202 tips to measure performance

202 tips for performance measurement

202 tips for
performance
measurement
practical ideas to choose, create and
use meaningful performance
measures with lots of buy-in!

Page 2 of 46 www.staceybarr.com


202 tips for performance
measurement
If you have a copy of this report without purchasing it from Stacey‟s website or without
subscribing to Stacey‟s free email newsletter, Measure Up, or without receiving a copy directly
from Stacey, then it is an illegal copy.

You can obtain a legitimate copy by subscribing to Stacey‟s free email newsletter, Measure Up,
which provides you with even more practical performance measurement tips twice each month,
at www.staceybarr.com.



202 tips for performance
measurement
practical ideas to choose, create and use meaningful
performance measures with lots of buy-in!

ISBN 1-921011-01-7
Written and published by Stacey Barr.
© Stacey Barr, 1999-2011

For additional information about how to make your performance measurement system a lot
more usable and a lot more useful, visit www.staceybarr.com and explore a wide range of
performance measurement resources.

Contact Stacey with your feedback about this book at info@staceybarr.com.

No part of this book may be reproduced, transmitted, re-posted or duplicated in any form or by any means without the
direct permission of the author and self-publisher, Stacey Barr. If you wish to quote a tip from this book, you may do
so providing you acknowledge the author where you quote that tip.

Disclaimer: The information provided is for the purpose of expanding the awareness of the reader of how to
effectively design, develop and use organisational performance measures and the author accepts no responsibility
for the subsequent use or misuse of this information.



thanks!
A heartfelt thankyou to those who gave me the feedback to improve this book and make it more
useful and more usable for others!

Vanessa
Suleman
Philip
Paul
Michael
Leona
John
Andrew

And my gratitude to those who took the time to share how 202 Tips For Performance
Measurement have helped them, in particular:

“Stacey, I have used some of the information that you‟re sending me in the mezhermnt ezine,
and guess what - I have used the 202 KPI tips ebook to cascade KPI‟s to all people reporting to
me. Since then we are always above target in terms of production.”
Alert Thovhokale, South Africa

“I just signed up to your website and downloaded your 202 tips file. Thought to tell you how
informative I found it. At 44 pages it took some focus but I read it from top to bottom. I have a
personal view that data is of no value unless you do something with it. Your tips have given me
several ideas on how to be a little more selective on what to measure and how to get the
analysis message across... Thought to let you know I really enjoyed the read and will be back
on the site searching for other items or interest.”
Steve Nolan, USA



contents
about the author, Stacey Barr .................................................................................................................... 7
how Stacey can help you ................................................................................................................................... 7
an introduction ............................................................................................................................................ 9
how to use this book........................................................................................................................................... 9
a framework for performance measurement ...................................................................................................... 9
phase 1: select useful measures of performance ............................................................................. 11
consciously adopt a performance measurement framework ............................................................................ 11
decide which outcomes are most worth measuring .......................................................................................... 11
design measures that provide objective evidence of your outcomes................................................................ 13
understand the relationships between and among measures .......................................................................... 14
define your measures to specify how to bring them to life ................................................................................ 15
phase 2: collect data with realistic integrity ...................................................................................... 17
understand your data requirements thoroughly ................................................................................................ 18
manage the integrity of your data ..................................................................................................................... 18
design cost-effective data collection processes ............................................................................................... 18
forms and questionnaires should facilitate easy, cost-effective data collection ................................................ 20
phase 3: store your data for easy access .......................................................................................... 21
standardise and organise your data to make it easy to find ............................................................................. 22
integrate your data to get cross-functional use out of it .................................................................................... 22
capture your data in a way that preserves its integrity...................................................................................... 22
access your data in preparation for analysis .................................................................................................... 22
phase 4: analyse performance data to create information ............................................................... 24
know the purpose of your data analysis ........................................................................................................... 25
summarising your data first helps you get to know it ........................................................................................ 25
explore your data for patterns (that‟s where the real answers are)................................................................... 25
test to decide which patterns you can trust ...................................................................................................... 26
phase 5: present your performance measures ................................................................................. 27
design graphs to make them useful for decision making .................................................................................. 28
decide the most useful structure and content for your performance reports ..................................................... 29
use layout and formatting to facilitate valid and easy decision making............................................................. 30
ensure your reporting process and tools support decision making ................................................................... 30
phase 6: interpret what your measures are saying ........................................................................... 32
know when a difference is really a difference ................................................................................................... 32
assess if you are on target (or not) ................................................................................................................... 33
phase 7: apply your measures to improve performance .................................................................. 34
use measures to review your plans .................................................................................................................. 35
be clear about the role of measures in decision making ................................................................................... 35
make improvement stick by fixing root causes ................................................................................................. 36
the most useful targets don‟t come out of thin air ............................................................................................. 37
overall: implementing your performance measurement system ......................................................... 38
engage the right people in the right ways ......................................................................................................... 38
integrate with other management processes .................................................................................................... 38
know what success will look like....................................................................................................................... 39
plan it like a project........................................................................................................................................... 39
references for further discovery .............................................................................................................. 41
in a bookstore ................................................................................................................................................... 41
on the internet .................................................................................................................................................. 45
ideas for where to next ............................................................................................................................. 46



about the author, Stacey Barr
Stacey Barr is the leader of one of the world’s largest performance
measurement practitioner networks, and a teacher and mentor for
corporate planners, business analysts, corporate performance managers,
and others who guide the development of meaningful, results-oriented
performance measures that focus their organisation on executing strategy
and achieving its purpose.
Since 1999, Stacey has been a freelance specialist in business
performance measurement - helping people to develop and use
meaningful performance measures to move their business or organisation
from where it is, to where they want it to be. And now, she sees her
primary role as giving this capability to others.
She’s the creator of PuMP® - the methodology that gives people the detailed practical
steps to develop performance measures – which compliments whichever framework they‟ve
chosen, be it Balanced Scorecard, Performance PRISM, or their own.
Stacey also publishes a free twice-monthly email newsletter, Measure Up, to share simple
but powerful tips to make measurement more meaningful.
With her consulting programs, public workshops, performance measurement practitioner
network and information products, Stacey has helped many organisations develop meaningful
performance measures more easily and with more buy-in than ever before.
Her goal is to help performance measurement practitioners build their performance
measurement capability, because it‟s one of the most critical and foundational systems any
organisation has.
Stacey’s clients know her for her passion and practicality. They include many federal and
state government agencies, local government authorities, corporations, non-profit organisations
and small to medium enterprises throughout Australia and New Zealand. She also has a
growing customer base internationally, particularly in the USA, UK and South Africa.

how Stacey can help you
Stacey‟s website, www.staceybarr.com, is renowned as a very practical and approachable
resource centre for information about how to meaningfully measure performance. In addition to
dozens of free articles she has written, you‟ll find information about her wide range of consulting
programs, public workshops and information products that can assist you in choosing, creating
and using meaningful performance measures:
 the Performance Measure Blueprint Workshop – a 2-day hands-on learning experience to
discover the 8 steps to implementing performance measures in your organisation or team
(www.performancemeasureblueprint.com)
 the Performance Measure Blueprint Online Program – a series of online lessons
supported by video presentations, case studies, templates and comprehensive lesson
workbooks which help you to discover the 8 steps to implementing performance measures in
your organisation or team (www.performancemeasureblupeprintonline.com)
 PuMP® How-to Kits – DIY step by step instructions, examples and templates to help you
easily and quickly master each step in the performance measurement process
(www.staceybarr.com/products)



How to Make Your Strategy Measurable – details the Results Mapping technique that
transforms the way your strategy is articulated and cascaded and aligned to measures
(www.staceybarr.com/products/resultsmapping.html)
How to Design Meaningful Performance Measures – details of the 5-step technique to
design great measures, even for those intangible or seemingly immeasurable results
(http://www.staceybarr.com/products/measuredesign.html)
How to Define Your Performance Measures – details of the technique to define the
specifications for how each of your measures will be implemented, so you have the
action plan to bring each one to life
(www.staceybarr.com/products/measuredefinition.html)
How to Design Useful and Usable Performance Reports – details of the technique for
presenting your performance measures and performance information so it focuses its
users on performance improvement (www.staceybarr.com/products/reportdesign.html)
 plus more – such as personal coaching, in-house consulting and more, at
www.staceybarr.com/products



an introduction
how to use this book
If you are looking for some extra ideas, for a way to reflect on what you have been doing
with performance measurement or for a quick reference to keep at the “tip” of your fingers,
then this little book will be worth keeping on your desk.
This book is not designed as an implementation guide for organisational performance
measurement, but as a supplement to what you already have in place to design, build and
implement your organisation‟s performance measurement system. If you want more specific
guidelines and “how to” information for organisational performance measurement, let me know
(staceybarr@staceybarr.com) and I‟ll do my best to help you find what you need.
Here are some ideas for how to use this book:
 If you are working on a specific aspect of performance measurement, such as designing a
report, working out data requirements, or trying to decide what to measure, read the
contents page to find the most relevant topic and read the tips in that section to help
expand or reinforce the approach you take.
 Bit by bit, build up your knowledge about what excellent performance measurement is, by
reading and reflecting on one tip per day or randomly flick through the pages and read
what jumps out at you or scan your eyes over the highlighted summary words in each
tip or open a page and read a tip while you are waiting on hold on the telephone, for a
train or bus, or while you eat lunch.
 Share the ideas with others involved in performance measurement activities, by taking the
book to your performance measurement development/implementation team meetings or
share a tip with someone you know who reports performance measures or someone who
uses them.
 Make yourself a coffee or hot chocolate or herbal tea and visit one of the internet sites
listed in the references.
 Read through the list of references in the back and take the book to your favourite
bookshop and have a look at the books that sound most useful or interesting to you.
It‟s all about gradually growing your knowledge and wisdom about how to create fabulous
feedback that helps you and your business improve until you really shine! I hope you have fun
and really benefit from using this book. I had a great time writing it – it always feels good to
reflect on your experiences and list out all the things you learned from them!

a framework for performance measurement
This book is a collection of the many mistakes and innovations and discoveries and learnings
that I have had over 10 years as an organisational performance measurement consultant.
Because there are so many of them (1001 to be exact), I have organised them into seven
chunks, each chunk being a phase in the Performance Measurement Process, or
PuMP® as it is more commonly known.
PuMP® comprises 7 phases that collectively encompass every activity you can possibly
associate with performance measurement:



Selecting what to measure means being centred on the outcomes that matter
1. select most to you and your business. Define your measures by carefully considering
what form the evidence of these outcomes takes.
The process of collecting data is critical to its integrity and can be very resource
2. collect intensive. It‟s worth giving serious consideration to how you will go about it, so
that your data can be “fit for purpose”.
Where and how you store your data directly determines what data you can
3. store access, when and how quickly you can access it, how easy or difficult it is to
access and how much cross-functional use you can get out it.
Analysis is the process of turning raw data into information. Make sure it is the
4. analyse most appropriate information by adopting the simplest analysis approach that
can produce the information in the form required to answer your driving
questions.
In communicating performance information, you are influencing which
5. present messages the audience focuses on. Take care to present performance
measures in ways that provide simple, relevant, trustworthy and visual answers
to their priority questions.
Interpreting your performance measures means translating messages
6. interpret highlighted by performance information into conclusions about what‟s really
going on. To turn information into implication, you must discern which
messages are real messages.
When you have worked out what is really going on with your organisation‟s
7. apply performance, you are ready to make some decisions about what to improve,
how much to improve it by and how to do that improving.

Each chapter focuses on one of the above phases of PuMP®, and it will begin with some more
information about that phase to set the scene for the tips that feature in that chapter.



phase 1: select useful measures of
performance
Selecting what to measure means being centred on the outcomes that
matter most to you and your business. Define your measures by
carefully considering what form the evidence of these outcomes takes.

When it comes to selecting performance measures, many people have simply brainstormed
measures they could potentially use, looked at the data they have available to see what they
could measure, adopted measures from other organisations in their industry or measured what
others told them to measure. None of these approaches has ever really lead to tremendously
useful performance measures that could claim to have enhanced organisational learning and
improvement.
The SELECT phase of PuMP® is about making the selection of performance measures more
conscious and deliberate with a focus on strategic direction or the outcomes that really matter.
It‟s topics cover:
 the fundamental framework that helps to identify the types of outcomes worth measuring
 designing measures so they are linked to (and provide objective evidence of) important
outcomes
 defining measures to remove ambiguity and fluff, and detailing how they will be brought to
life

consciously adopt a performance measurement framework
tip 1: When you select a performance measurement framework, check that its underlying
premises and assumptions align with the culture and vision of your organisation. Make
sure that what you measure is motivating and meaningful for the stakeholders of your organisation.
tip 2: The Balanced Scorecard by Kaplan and Norton [ref 5] doesn‟t tell you HOW to measure, it
helps you decide WHAT to measure. It is only ONE of many different frameworks for deciding
what to measure. Have a look around to see what else you have to choose from: The Performance
Prism [ref 21], OPM® [ref 31], Triple Bottom Line, EFQM [ref 32], ABEF [ref 33], Malcolm Baldrige
Award [ref 34],… what else can you find?

decide which outcomes are most worth measuring
tip 3: Many organisations believe performance measurement is about measuring people.
Performance management, performance appraisal and other terms are used for the same thing. If
you want a high performing organisation, then don’t measure people, measure processes and
outcomes instead. The organisation works for the people, not the other way around, as many believe
and have never questioned. Dare to test your assumptions about this by reading books like Peter
Senge‟s “The Fifth Discipline” [ref 8], Tom Coen‟s and Mary Jenkins‟ “Abolishing Performance
Appraisals” [ref 1], Margaret J. Wheatley‟s “Leadership and the New Science” [ref 16] and Margot
Cairnes‟ “Approaching the Corporate Heart” [ref 4].
tip 4: Try to pay attention when people seem to be hesitant to measure something –
you might even hear comments like “if we measure this, it might show how bad things are” or “let‟s



measure the things we are doing well”. These kinds of comments are symptomatic of a few things, in
particular a lack of appreciation that measurement is not about proving, it‟s about improving.
tip 5: People‟s reluctance to measure things can also be symptomatic of an unhealthy
performance culture, where blame and scape-goats dominate over curiosity and innovation. Do what
you can to reinforce that performance measures are feedback about the systems and processes and
behaviours, performance measures ARE NOT feedback about people.
tip 6: If you are stuck for what to measure, try starting with listing all the stakeholder
groups of your organisation (or department or process), then find out for each stakeholder group
the 2 or 3 attributes that are currently most important to them about your organisation (or department
or process) and are currently not performed very well by your organisation (or department or
process). Measure and improve those attributes.
tip 7: A very clear, concise strategic direction is essential before you can expect to develop really
useful performance measures. Make sure your vision, mission, strategies and goals are all worded in
rich, descriptive, “sensory based” language [ref 14] that evokes clear mental experiences of
what the future will be like when you have achieved them. These descriptions will make it easier to
select measures.
tip 8: Kaplan and Norton introduced the term strategy mapping [ref 27] which is a method of
laying out the various components of a strategic direction and examining the relationships between
them. The Balanced Scorecard [ref 5] is their template for identifying and categorising and linking
components of strategy, but the same concept is useful even if you don‟t subscribe to the Balanced
Scorecard. The basic idea is to visually map all the specific outcomes needed to bring
your strategy to life, linking them together in cause-effect and companion relationships. Read
more about a transformational and engaging method, called Results Mapping, which makes it easy
to focus on the results that matter and cascade them throughout your business or organisation, at
www.staceybarr.com/products/resultsmapping.html
tip 9: Define each outcome or result or entity before designing the measure or expect
to spend a long time debating the measure and to end up with a measure that is not going to give
you the feedback you really need. Begin with the end in mind, and Stephen Covey [ref 23] would say.
tip 10: Stocktake your existing performance measures by placing them in a matrix based
on the level of decision making they best serve (strategic, tactical or operational) and the stakeholder
group they best respresent (shareholders/owners, customers, employees, partners, communities).
Where are the gaps? Where is the oversaturation?
tip 11: What are your organisation‟s values? Would improving performance based on your
current performance measures mean you would be living your values, or working in conflict
against them?
tip 12: If you want to measure the effectiveness of your projects or other change
initiatives, and realise that “on-time” and “on-budget” measures do nothing to help (they only
measure a couple of dimensions of efficiency), then use tip 16: to help you develop some measures
for how the project will impact on the business, how the project is tracking against its objectives and
how well the project‟s strategies are working.
tip 13: If you can help people understand processes and process thinking, they will
find it much easier to decide what to measure for feedback into the operational level of decision
making. They just have to define their process and assess how it impacts on the organisation‟s
current strategic direction.
tip 14: Help people understand how their work impacts on others such as internal or
external customers, internal or external suppliers and other stakeholders as clues for what might be
important to measure.



design measures that provide objective evidence of your
outcomes
tip 15: Remember that performance measures are “objective evidence of the degree to which an
outcome is occurring”. How much objectivity or subjectivity do your measures have? What
kind of evidence forms that basis of the measures‟ values?
tip 16: If you want performance measures to be owned and used, then the people to own
them MUST be involved in the processes of choosing the measures and defining them.
tip 17: If you have identified a really useful measure, make sure you also identify which person
or people will be responsible for using the measure. Measures have to be used if they are going
to lead to improvement.
tip 18: What do you do if you believe something can’t be measured? Well don‟t give up
straight away – most people don‟t realise you can just follow a simple process to come up with some
potential measures fairly quickly. First, describe the outcome to measure. Secondly, make it sensory
specific – detail how it would look, feel, sound if it were happening. Thirdly, brainstorm all the different
things you could count (the evidence) that would prove the outcome was occurring. These counts are
your potential measures. Choose the most direct, objective and feasible. You can read more about a
very logical, powerful and engaging Measure Design technique at
www.staceybarr.com/products/measuredesign.html
tip 19: Often people will say “we can’t measure that because we don’t have the data for
it”. Be warned – if you don‟t start trying to measure important things, you will NEVER have the data
your business needs. Performance measures are one of the ways that decision makers articulate
their data needs to the IT people who are trying to design information systems that align with
business decision making.
tip 20: Are you trying to measure too much? Any one person can really only effectively focus on
at most 72 (that is, between 5 and 9) [ref 14] performance measure at any one time. More than
that and no one measure will likely be managed well at all.
tip 21: If you like TOC (Theory of Constraints) thinking, then you might connect with the approach
to measurement that Eli Goldratt offers. It is simply based on using three measures of business
performance, Throughput, Operating Expense and Inventory, as the basic building blocks
of management information.
tip 22: A lead indicator is a performance measure that gives you forewarning of an impending
change in another performance measure (the lag indicator). Usually they are measures of results or
outcomes of activities or steps that occur in the early stages of a process (or chain of events) that
produces the result or outcome tracked by the lag indicator. To find useful lead indicators, you
need to flowchart or map or diagram the chain of events that lead to your lag indicator and test which
steps in this chain are the most influential on your lag result.
tip 23: To be useful, you need to track your lead indicators with greater frequency than
the lag indicator they “predict”.
tip 24: Don‟t aim for a perfectly complete set of performance measures before you start bringing
them to life. Instead, adopt an action learning process whereby you focus on a small number of
measures first, bring them to life (which will iron them out a little more) and then use them to see if
they add the value you anticipated. Learn from this entire process and use this learning to bring to life
and use another set of measures.
tip 25: It‟s better to have an imperfect measure that captures the essence of what you are
trying to measure than not measuring it at all. Using the action learning approach (tip 24:) so you can
build some momentum and accelerate your learning.



tip 26: To get a head start on selecting measures, do a little industry research to find out other
“best practice” organisations are measuring things. But DO NOT adopt any measure unless
it directly supports your strategic direction! It actually helps if you have formulated your strategic goals
or objectives before doing this kind of research.
tip 27: Avoid so-called measures such as “completion of plan by June 06” or “new IT system in
place”. These are milestones or events and not measures at all (nothing is being counted over time
and there is no real comparison to gauge change). They are not really outcomes but more the
chosen means toward the outcome. Many an IT system has been put in place and not delivered it‟s
intended outcomes! Always measure outcomes, not events or milestones.
tip 28: Whatever you do, don’t rely on brainstorming as a method for coming up with
measures. It‟s too easy to go off track or end up listing potential measures that are no better than any
measure you have ever used in the past. The best measures are measures that provide direct and
objective evidence of the outcomes you want to track, so use tip 16:.
tip 29: Involve some people from outside the area of the business you are trying to measure to
help you get a fresh perspective. Encourage them to ask “dumb questions” that challenge your
current thinking and reframe the ways you look at the purpose and outcomes of that area of the
business.
tip 30: Criteria for deciding whether or not to take up a measure can really help clarify the
selection process. Criteria might include: strength of alignment to strategic direction, cost-benefit of
data collection, degree of influence you have over it, level of complexity or understand-ability, etc…
tip 31: When you choose a measure to track a particular outcome, ask the question “what
kinds of behaviour could this encourage people to choose?” as a way to check that
measuring the outcome won‟t create any other performance problems (you know, you measure cycle
time and everyone does their best to work faster at the expense of reliability of their work or quality of
their relationships with customers or other stakeholders).
tip 32: It‟s becoming common knowledge now, but check that you have a balance between
measures of financial performance and measures of non-financial performance.
Financial measures are very lag, and make it hard for you to anticipate problems before they
eventuate.
tip 33: It is possible that you might end up with a set of measures that track your current strategic
direction AND a set of measures that track “business as usual”, which are outcomes you want to
maintain or keep an eye on even though you have no current intention to improve them as part of
your strategic goals.
tip 34: Do people in your organisation have a tendency to measure the easy stuff? You
know, the number of inquiries, the number of transactions processed, the number of calls answered,
and so on? These are activity measures, and while somewhat useful for workload management, they
are not outcome measures and thus do not drive performance improvement. Often you have little
control over them anyway.

understand the relationships between and among measures
tip 35: Map the linkages between measures used at different levels of decision making in
your organisation, to show the “line of sight” of operational measures up to tactical measures and
then to strategic measures. This measurement map will be useful to see at glance what is measured
throughout the organisation and how integrated the set of measures is. It‟s very similar to Results
Mapping, where you link and cascade performance results throughout your business or organisation,
and you can read more at www.staceybarr.com/products/resultsmapping.html
tip 36: Your measurement map (tip 35:) can act as a road map for cause analysis and
strategy implementation. If you are responsible for a small collection of measures, then look at



the relationships your measures have to others. Which measures are counting on you to improve
your measures before they can improve? Which measures would you look to for leverage to improve
your measures? Which measures should you be wary of inadvertently affecting through improving
your own?
tip 37: Your measurement map (tip 35:) can help everyone in the organisation
understand how they influence organisational success and sustainability. By
understanding which measures they directly affect, they can follow the linkages through to the
strategic level to understand why their improvement actions matter.

define your measures to specify how to bring them to life
tip 38: Define each of your measures so that it is clear what they really mean. Consider
writing a description, their intent, who owns them, how they are calculated, what data items are
required to calculate them, how they will be charted and reported, and what kinds of responses
should be taken depending on which “signal” the measure gives.
tip 39: It helps to have a single, standard, organisation-wide template for defining
performance measures. It will make it easier to manage all the measures and more efficient to report
them (see phase 5:). Read more about the step by step framework for defining your performance
measure details, so each measure has an action plan to bring it life and report it, at
www.staceybarr.com/products/measuredefinition.html
tip 40: When you define the intent of each measure, think about what business question
you are trying to answer with it, or what action you can‟t take unless you have this information.
tip 41: When you define the calculation formula for each measure, try to be as
mathematical as possible to identify each data item that will be needed. For example, [sum
(satisfaction_rating) / count (respondents)] is better than “average customer satisfaction”. This makes
the sourcing of the data items less ambiguous and thus less likely for your measure‟s integrity to be
compromised.
tip 42: When you define the owners of each measure, consider different types of
ownership, such as the owners of the data items, the owners of the definition itself and the owners of
the performance area being measured (usually the one who uses the measure).
tip 43: One way to check whether to invest in a particular performance measure is to describe
exactly how it will be used and interpreted – if you can‟t see any action or decision being
taken as a result of using the measure, then there‟s probably not much point bringing it to life. The
time to do this is when you are defining the measure, after you have defined its intent (tip 40:),
calculation (tip 41:) and owners (tip 42:).
tip 44: When everyone has an opinion about the "shoulds" of a measure as you try to
define it, there's a good chance that you haven't converged on the specific entity you need to
measure.
tip 45: Keep your performance measure definitions in a “dictionary” so people can
keep up to date on the meaning of each measure, keep track of changes made to measures, quickly
identify which measures are currently most important and have a specification for how to consistently
calculate and report the measures. Make sure your dictionary is based on a clear and complete
method for defining each performance measure, like the one described at
www.staceybarr.com/products/measuredefinition.html
tip 46: I use a Microsoft Access database for performance measure definition
dictionaries which I share with clients. It makes it easier to search for specific measures, track
them using a unique identifier and produce action plans for data collection and sourcing from the data
items section in the definition.



tip 47: Make a very conscious decision about where you write your performance targets:
in your performance measure definitions, in your performance reports or in your business plans? A
conscious decision means you have a clear rationale or reason.



phase 2: collect data with realistic
integrity
The process of collecting data is critical to its integrity and can be
very resource intensive. It’s worth giving serious consideration to how
you will go about it, so that your data can be “fit for purpose”.

It‟s too easy to limit your choice of performance measures just to the data you already have
available. It‟s a quandary, because we all know that the only way we can get the data we really
need is to ask for it. That‟s why the COLLECT phase of PuMP® is so important. It provides the
mechanisms for how to collect the data we don‟t already have, but really, really need.
Using performance measure definitions as the starting point, the COLLECT phase focuses on
topics including:
 defining very specifically and clearly the data requirements for each measure
 understanding and managing data integrity
 designing and implementing cost-effective processes for collecting data
 designing forms and questionnaires that support data collection and preserve integrity



understand your data requirements thoroughly
tip 48: Check your performance measure definitions to see how frequently the data items
for each measure are required. Are the measures calculated daily, weekly, monthly, quarterly or
annually? Can your data collection processes deliver data at the required frequency, or do you need
to revise the measure? If you don‟t have clear and complete definitions for your measures, then learn
how to at www.staceybarr.com/products/measuredefinition.html
tip 49: Tabulate a summary of your data item requirements by collating them from your
performance measure definitions (see tip 38:). List the data item names, descriptions, which
measure(s) they are required for, the source system (such as a database, if one exists) and whether
or not each data item is currently available and has sufficient integrity.
tip 50: Where your data item requirement summary (tip 49:) shows you need data that is not
currently available, you will probably want to consider designing a data collection process to make
it available. Read on for more help!
tip 51: Where your data item requirement summary (tip 49:) shows you need data that does
not have sufficient integrity, you will probably want to consider improving its data collection
process to make build in more integrity. Read on for more help!

manage the integrity of your data
tip 52: It might help to ask users of your performance measures how much integrity
they require of the measures (not how much they would like!). What percentage or amount of error
can the measure have before it becomes dangerous or useless? For example, is 5% too much error,
or is 10% still okay? This will depend on the importance of the decision being made and how
sensitive it is to small changes in performance levels.
tip 53: Don‟t rely on data from volunteer surveys, like mail surveys. Response rates of 9% (for
example) can not be trusted to give you objective information.
tip 54: Just because you got a response rate that was “unusually high for this type of
survey” doesn‟t mean you got reliable data!
tip 55: Good survey data can only come from a randomly selected sample. Otherwise your
data is biased. What happens if you make a decision based on biased data? You usually get different
results to what you need or expect, and that almost always means wasted money, time and effort.
tip 56: A good sample size IS NOT a particular percentage of a population. If you have 1000
employees and you want to survey their satisfaction, a 10% sample size is a purely arbitrary
decision. Your sample SHOULD depend more on how much variation in responses you are
expecting (the more variation, the bigger the sample size) and how reliable you want the estimates to
be (the more reliability you want, the bigger the sample size).
tip 57: Survey statisticians and market researchers will have a formula that will help you
calculate your ideal sample size based on what you are trying to measure through the survey.
tip 58: You can actually measure the amount of integrity your existing data has, by way
of a data audit. This usually involves taking a sample of records or data items from your database
systems and checking them against the original sources (such as people, forms or objects) for such
things as completeness (e.g. missing values), accuracy (e.g. typing errors) and precision (e.g. the
amount of detail). Ask your business or quality auditors for advice.

design cost-effective data collection processes



tip 59: Well designed data collection processes produce data with integrity: relevance, reliability,
representativeness and readability, realistically (or cost-effectively). You will need to make a
conscious decision about how much you will invest in your data collection process and
how much integrity the resulting data will have.
tip 60: If you are designing a new data collection process, involve the people that will own
or do the data collection in the designing. Refer also to the “data owners” that might be nominated in
the corresponding performance measure definition.
tip 61: It is important to carefully define the scope of the population you are collecting
data from, or your data will end up being “diluted” or only a partial representation of what you are
trying to measure. For example, if you want to measure the cycle time of order processing, don‟t just
measure one person or one team: your scope is all orders that are processed and so your data
collection should cover this entire scope (even if you just take a random sample).
tip 62: If you are finding the data collection effort for your defined scope (tip 61:) is going to be
too overwhelming, then consider narrowing your scope for a while until the data collection
process becomes familiar and bedded down. Then you might try widening the scope again. Just be
sure that when you report your performance measures, you note the scope that the measure applies
to.
tip 63: Where can you automate data collection? Can a computer do what a paper form is
currently doing? Can an existing form be modified a little to capture the new data you want?
tip 64: Flowchart your data collection process(es) to understand how they currently work,
and therefore how you can modify them to improve data integrity, data availability, data timeliness, or
the impact the data collection effort has on people who work in that process.
tip 65: When your data is collected, where does it go? Straight into a database system, or does it
sit in a pile somewhere, or several piles in several places? Data is a precious asset for any business,
so take a deliberate approach to how data is collated and captured after it is collected.
tip 66: Always pilot test your data collection processes before “going live”. This always
surfaces things you can‟t anticipate, such as ambiguities on forms or questionnaires, confusion in
exactly how to collect the data, practical constraints that prevent the data being collected in the way
you planned or that the data you collect isn‟t really what you need.
tip 67: When your data collection process has been designed, tested and had the bugs ironed
out of it, document it so becomes a resource to those involved in the data collection process,
which can help keep the collection consistent as time goes by.
tip 68: If you are collecting data from stakeholders of your organisation, such as employees,
customers, shareholders, communities or strategic partners, consider outsourcing the data
collection process to help respondents feel that they can be candid and their confidentiality won‟t
be compromised.
tip 69: Are you collecting more data than you need? Data collection certainly costs time
and effort and money and there are so many examples of data collection processes that capture too
much “interesting” information and not enough “useful” information. Apply the interesting-versus-
useful test on each data item your organisation collects (not necessarily all at once, of course).
tip 70: Consider (carefully, to avoid going overboard) what supplementary data you might
need in addition to the performance measure data you are collecting. Supplementary data can be
analyse to provide a context in which to interpret your measures, by answering questions such as
“what caused this change?” or “where is this happening the most?” or “is this result the same for all
customer segments?”.
tip 71: Who else might be already collecting the data that you need? Another business?
A government department? A market research agency? Your suppliers? A university or business
school? An industry association? Why duplicate effort?



forms and questionnaires should facilitate easy, cost-
effective data collection
tip 72: Have you looked at the design of forms used to collect data in your organisation
lately? Look for any opportunities to make them less ambiguous, simpler, laid out in a way that is
easier to navigate and use. The design of your forms affects the integrity of your data like you
wouldn‟t believe!
tip 73: Make sure that each field or question on your forms or questionnaires focuses on a single
construct. For example, instead of asking “Are our products exciting and useful?”, ask “Are our
products exciting?” and “Are our products useful?”. This will reduce the ambiguity in your form
and thus improve the integrity of your data.



phase 3: store your data for easy access
Where and how you store your data directly determines what data you
can access, when and how quickly you can access it, how easy or
difficult it is to access and how much cross-functional use you can get
out it.

PuMP®‟s STORE phase is about how your organisation captures and retains and manages and
makes available the raw data that it captures. For performance measurement to work well,
timely access to a diverse selection of data is essential, so data management systems need to
be designed in a way that makes it easy to find the data you need, and easy to extract it to.
The STORE phase of PuMP® addresses the topics of:
 standardising data items across the whole organisation
 organising data into logical tables or repositories
 being able to link data from different tables or repositories together, to answer those “cross
functional” questions
 accessing data in preparation for analysis



standardise and organise your data to make it easy to find
tip 74: If you are collecting new data, consult with your IT person or team before buying or
building a new database system. Try to integrate with the database systems you already have.
tip 75: A data dictionary can be very useful when designing new measures. Like a
menu, it lists all the data items available in the organisation, where they can be found, what format
their values take, how regularly they are collected, and so on. Very useful if you want to avoid
duplicating your data collection efforts.
tip 76: Avoid keeping your organisation‟s data stored in informal, independent systems like
spreadsheets or applications custom made for specific projects. You get a much higher return
on your data when it can be shared and used around the organisation.

integrate your data to get cross-functional use out of it
tip 77: Many organisations have trouble linking data across organisational
boundaries. This is often the case when there are no standard conventions for uniquely identifying
data entities like assets, customer orders, employees or cost items. If you wanted to know the cycle
time of processing customer orders, you‟d have to be sure that the code used to name each order by
the sales people who receive the order was the same coding convention used by the people who
fulfil the order. If not, you can‟t match up the received date with the completion date of each order
without a LOT of manual work.
tip 78: Getting access to data is equally important as capturing it. The way that data is
captured in a database system or other format (such as a spreadsheet), limits how easy it will be to
“pull it out” again so you can analyse it and create the values of your performance measures.

capture your data in a way that preserves its integrity
tip 79: Data entry is one point where data integrity can be compromised. Are there
ways that you can get data entry software to automatically detect some of the data entry errors that
occur, such as values out of range or values not in a predefined list?
tip 80: What are your organisation‟s protocols for protecting confidential data? Do they
prevent you from sourcing data for a particular performance measure, or are you able to still calculate
the values of your performance measure without compromising confidentiality?
tip 81: Who has access to data and who doesn’t is an important to decision to make, in
order to prevent the data‟s integrity from being comprised and to manage confidentiality.

access your data in preparation for analysis
tip 82: How much historic data is kept before being archived is one factor that can really the
limit the quality of analysis you can do on your performance data. Most analyses of time series data
(the majority of performance measures are of this form) require a minimum of 20 to 30 consecutive
performance values. This means for a typical monthly measure, you will only get a good quality
analysis if you have 2 to 3 years worth of data.
tip 83: Sometimes the process to actually extract or source the data for your
performance measures can be too difficult or technical without the help of an IT expert.
Consider working with the experts to create some simple macros or queries that you can easily run
each time you need to calculate the latest value for your performance measure. Better still, how can
the calculation of your performance measures be automated entirely?



tip 84: Data analysis (to create your performance measure values) almost always requires that
you take (copy, really) a chunk of data out of its source system and put it into the analysis package
you will use. Think very carefully to understand the format you need the data in to analyse
it before you extract or pull that data out of its source systems. For example, do you want transaction
level data, or summary level data such as weekly totals.



phase 4: analyse performance data to
create information
Analysis is the process of turning raw data into information. Make sure
it is the most appropriate information by adopting the simplest analysis
approach that can produce the information in the form required to
answer your driving questions.

Raw data is virtually never useful for assessing the performance of a process, system or
organisation – it‟s just too detailed. Because of natural variation, more information comes from
patterns in datasets than from individual points of data alone. That‟s why the ANALYSE phase
of PuMP® is so important – it is the process that turns the raw data into the information our
performance measures are intended to provide.
There are a few important topics associated with the ANALYSE phase of PuMP®:
 being clear about the questions you want the measures and their analysis to answer
 understanding the different processes of analysis (summarising, exploring, explaining and
predicting) and when to use them



know the purpose of your data analysis
tip 85: Write down the questions your performance measures and information are supposed
to answer before deciding what kind of statistical or analysis technique will be most appropriate.
tip 86: Find out who will be the users of your performance measures and ask them
what questions they want the measures to answer.
tip 87: Find out the questions that users of your performance measures have and are
expecting the measures to answer for them, and then choose analysis and graphical methods that
best answer these questions.

summarising your data first helps you get to know it
tip 88: Before you analyse your performance data, have a closer look at it. Check for whacky
values that might be errors or typos, check that the amount of data is typical for that period, and if you
find anything weird, check it out with the people that collect the data. This is called “cleaning your
data” and will help you maintain the integrity of your performance measure.
tip 89: One of the first things to do in data analysis is to get to know your data by summarising it
by calculating simple statistics like its average, minimum and maximum values, median, mode, 25th
and 75th percentiles and standard deviation. These simple statistics help you understand the
shape of your data, so you are less likely to be misled by the mean.

explore your data for patterns (that’s where the real answers
are)
tip 90: A mean or average doesn’t really tell you enough about the level of performance.
Accompany a mean with other statistics that give you a feel for the shape of variation in the level of
performance, such as the standard deviation, the range, the mode or median, or the quartiles (the
25th and 75th percentiles). You can find out more about these statistics in any good business statistics
book or by looking for statistics pages on the internet.
tip 91: Avoid using straight counts or tallies as the values of your performance measures
(such as the number of transactions processed). Performance is almost always a relative thing, and
thus you get more information when you use rates or percentages or averages (such as the number
of transactions processed as a percentage of the total number of transactions received, the number
of transactions processed per employee).
tip 92: Remember that performance measures are most useful when you are tracking a
specific result over time in a regular way. This will help you understand the dynamics of
performance levels, that is, how much the level naturally varies over time, when the level is changing,
and when something abnormal happens.
tip 93: Analysis of performance data is more than just computing the values of your performance
measures – it‟s also about providing a context or explanation around your performance
measures. Consider supplementary information like a Pareto analysis of the potential causes of a
change in performance, or a breakdown of your performance measure by some relevant classifying
factor such as region, customer segment or business process. These supplementary analyses may
require you collect a little more data (see tip 70:).
tip 94: If you want to explore causal relationships between measures, then try techniques
like scatter plots or correlation or regression analysis. These analyses test the strength of the
relationship between variables, but beware: just because there is a relationship, doesn‟t mean it is a
causal relationship! Use your common sense and curiosity to inquire further.



tip 95: Did you know that you need a bare minimum of 20 consecutive performance
values before you can even begin to do a reliable trend analysis? In fact, you‟ll often need even
more than 20 before you can see the “big picture” pattern of variation in your performance values.
tip 96: If you are tracking your performance measures over time, then statistical process
control charts will be really useful for you – they make it really straightforward to decide how
much the level of performance naturally varies over time, when the level is changing, and when
something abnormal happens. A little more information about SPC charts are provided in tip 97: and .
tip 97: When you have your minimum of 20 consecutive performance values, and they show a
reasonable amount of stability over time (i.e. no big changes or shifts), then calculate the mean
(average) of these values and put a straight, horizontal line for this mean through a time series chart
(line chart) of your performance values. This mean line is a good benchmark for deciding when
performance really is changing – or not. Don‟t recalculate this mean line until you see a
signal. The following tips tell you about the signals.
tip 98: If you have implemented tip 97: where you added a mean line to the time series chart of
your performance measure values, then you might like to add some additional, useful benchmark
information, called control limits. The control limits show you how much variation you can
expect from your current level of performance, unless something fundamentally changes
(like you change the process producing that performance). The control limits are simply calculated as
3 standard deviations above and below your mean line.
tip 99: After getting to know your performance data (tip 89:), looking for patterns is often what
happens next. To explore your data for patterns, try analysis methods like scatter plots, line
charts, bar charts, box plots and correlation coefficients.

test to decide which patterns you can trust
tip 100: When you have found some patterns in your performance data (tip 99:) that you would like
to draw some conclusions from, you can test the significance of patterns using techniques like
regression analysis, analysis of variance, and other tests of comparisons like t-tests.
tip 101: If you just can‟t live life without linear trend lines (I suggest you should find a way), then
always report the R2 (r-squared) statistic with the trend line. This statistic takes a value
between 0 and 1 (or 0% and 100%) and effectively tells you just how good your linear trend line is at
conveying the message in the data. The lower the R2 value, the less confidence or trust you should
place in your trend line as any kind of useful conclusion about what performance is doing.
tip 102: If you have a theory about a potential lead indicator for a performance measure (such as
cycle time as a lead indicator of customer satisfaction, or customer satisfaction as a lead indicator for
profit), find out more about how correlation analysis can help you test the “lead indicator
strength” in predicting what the performance measure will likely do in the future.
tip 103: Be wary of data mining applications. They don‟t replace the need for performance
measurement (well, not yet anyway). Performance measurement needs to be a very conscious
process, where you deliberately seek the answers to business questions around the achievement of
goals. Data mining is a more exploratory method of analysis to surface potential trends or patterns
you were otherwise unaware of. These trends or patterns may not necessarily mean anything, either.



phase 5: present your performance
measures
In communicating performance information, you are influencing which
messages the audience focuses on. Take care to present performance
measures in ways that provide simple, relevant, trustworthy and visual
answers to their priority questions.

This phase of PuMP® is about how you design graphs and visual reports that present
performance measures to their audiences. It‟s important to be aware of how they will use the
measures, how to make the measures easy to interpret and how to not overload the audiences
with too much detail!
The topics relevant to the PRESENT phase of PuMP® include:
 choosing the right graph type
 formatting graphs to ensure integrity, simplicity and a focus on patterns, not points
 designing performance reports that are easy to access, easy to use and targeted at the
needs of those that use them



design graphs to make them useful for decision making
tip 104: Don’t take your graph design for granted! The design of your graphs has a HUGE
impact on how well they are used, IF they are used, and the validity of the conclusions users draw
from the data they present.
tip 105: The purpose of graphs are to make huge amounts of quantitative information more easy
to digest. So, keep your graphs as simple as possible or they won‟t be adding anything useful
to your ability to use your performance measures wisely and effectively.
tip 106: To keep your graphs simple, try getting rid of what Edward R. Tufte [ref 21], a visual
information expert, refers to as “chart junk” – all the stuff on your graph that uses ink but doesn‟t
add useful information. Typical chart junk includes grid lines, extra tick marks, long titles and
explanations, self-explanatory legends, borders, kooky fill patterns (like checkers or stripes).
tip 107: If you use gridlines in your graphs, ask yourself the question, what purpose are do the
gridlines serve? If it is to encourage users to focus on the value of individual points of data, then
why do you have the graph? Graphs are about highlighting patterns and signals and are not
supposed to be another form of a table.
tip 108: If you must use them in your graphs, make sure your gridlines are very fine and light
in colour so they can serve their purpose without dominating the data.
tip 109: Do you need that many tick marks? Are they really helping, or are they just cluttering up
the graph?
tip 110: Graphs are not a canvas for artwork, they are a canvas for patterns and signals in
quantitative information. Little piles of coins don‟t make useful bars in your bar chart of revenue or
expenses.
tip 111: Avoid using 3-dimensional charts as they have a tendency to confuse the eye with
the addition of sloped lines to produce the 3-D effect. Nice straight horizontal and vertical lines are the
best for visual comparisons.
tip 112: There are some useful things to include in your graphs to help users interpret and
understand what they are looking at, like a title or axis labels that clearly explain the measure being
charted, a legend if you are reporting more than one variable, a footnote that clarifies the scope or
exclusions of your measure and sometimes even the source of the information or data is helpful.
tip 113: Do you ever chop out the middle or chop off the bottom of your scale on the
vertical axis? So instead of starting at 0, you have your axis starting from something like 350 (for
example)? This practice over exaggerates any patterns or signals in your data, and may lead users
to draw invalid conclusions.
tip 114: Avoid using pie charts to report performance. Pie charts are very good for
prettying up your annual reports or marketing material, and sort of good for showing how big a single
part is relative to its logical whole, but are pretty much awful at helping you make performance
improvement decisions.
tip 115: Bar charts work best with between 5 and 9 bars and for the purpose of comparing
the size of elements to one another. Avoid using bar charts for time series data – they just look like
mountain range silhouettes, not trend information.
tip 116: If you have charts that have stacked bars, grouped bars, area charts or line charts with
more than 3 lines on them, you have information overload. It will take users quite a while to figure out
what the chart is trying to achieve, and they will be forced to look at individual numbers to figure out
trends or patterns. One chart per performance measure.
tip 117: To make your statistical process control charts look a little less cluttered, try
making your mean line light grey and solid, and your control limit lines light grey and dashed, both



without symbols. The line for your performance measure values can then take pride of place by using
colour and symbols to your liking.
tip 118: Consider designing a standard graph template for each graph type you will use to
display your measures. A standard look and feel helps the strengthen the focus on the information,
and minimise the distraction of formatting differences. Standards like these can be applied
corporately. Read more about how to make your graphs useful for decision making, and get a
template of sample graphs that work, at www.staceybarr.com/products/mgu.html

decide the most useful structure and content for your
performance reports
tip 119: How do you report your performance measures? Have you taken a conscious approach to
designing how performance measures are collated and arranged and narrated in performance
reports? What is your rationale for how performance measures should be reported or
displayed to their users?
tip 120: Design the contents page of your performance reports before you design
anything else – this will help you set up a useful and usable structure for the report before you get lost
in the detail. Did you know that the contents page of a performance report can become an executive
summary? You can read more at www.staceybarr.com/products/reportdesign.html about my how-to
kit for designing useful and usable performance reports, which includes templates of great reports
you can use as your starting point.
tip 121: Identify all the users of your performance measures before designing your
performance report – you may need different formats of the report depending on the type of user.
tip 122: Interview users of your performance measures to find out what needs the
performance report has to satisfy, such as how frequently they need it, what they need it for,
how much time they want to commit to using it, what specific questions they are wanting it to answer,
what format best suits them (see tip 135:) and so on.
tip 123: Don‟t succumb to all the needs of the users of your performance measures – report
design is not all art, it’s a science as well. If you want it to still be useful, avoid including
someone‟s idea just to avoid hurting them or being politically correct. The best thing you can do for
such people is help them make the best use of their information.
tip 124: Decide the theme of your performance report. Don‟t just lump a whole lot of measures
together without thinking about the decision process that it should serve. Consciously decide your
rationale for which measures to include and which to exclude.
tip 125: If the commentaries in your performance reports consist mainly of explanations about why
targets weren‟t met or why this month is worse or better than last month, then they are not too far
from useless. Managing performance means managing the trends and patterns, not events. How
could you put more information about the trends and patterns in your reports, and less
of the ad hoc trivia that suggests you never need to, or are able to, do anything to improve
performance?
tip 126: Put a contact name with each measure in the performance report so users can
follow up if they want more information. This might be the owner of the measure, as documented in
the measure‟s definition (see tip 38:).
tip 127: Consider if it would be useful to include with each measure in the performance
report its description, as documented in the measure‟s definition (see tip 38:), to remind users
what the meaning of the measure is, so they are less likely to jump to the wrong conclusions.



use layout and formatting to facilitate valid and easy decision
making
tip 128: Colour can really help information jump off the page in your performance
reports. Red can strongly communicate unacceptable performance, green for improving or
acceptable performance and orange for early warnings about likely future results.
tip 129: Some of the more useful types of information to include in a performance report
include the graphs of the measures, brief comments about any patterns or signals the graph is giving,
what the causes of the patterns or signals are and comments about what is being done to respond to
the patterns or signals (if a response is required).
tip 130: Carefully design the page layout to give a consistent look and feel throughout
your performance report. Consider where you will place graphs, interpretation comments, cause
analysis, action updates and so on. This helps people navigate through the report and find the
information they are looking for.
tip 131: At your local library or bookshop, look for books on graphic design and layout to
get ideas and example for making your performance reports professional, simple and incredible
usable. A good one is The Non-Designer‟s Design Book [ref 18] by Robin Williams (no, not the actor).
tip 132: Try designing your performance reports with one page per measure and include
the title of the measure, a graph, a simple comment interpreting the graph, and a brief cause
analysis. This way you can pull together different collections of performance measures for different
users.
tip 133: Play around with interpretation flags, little icons that symbolise visually and rapidly
what each performance measure is doing. For example,  can mean that performance is in balance
and where it should be,  can mean that performance is headed in the wrong direction and needs
immediate attention,  can „flag‟ if there is an early warning of poor performance and  can
symbolise improvement.
tip 134: Keep your performance reports as visual as possible, avoiding lots of text. This is
time consuming and often doesn‟t tell the user much that they really want to know, or couldn‟t find out
by talking to someone if they felt they needed to. Focus on graphs, interpretation, cause identification
and action progress. You can read more at www.staceybarr.com/products/reportdesign.html about
my how-to kit for designing useful and usable performance reports, which includes templates of great
reports you can use as your starting point.

ensure your reporting process and tools support decision
making
tip 135: However you choose to disseminate your performance reports, be conscious of how
people will want to and be able to access them. Convenience, literacy, technology and
location all have a bearing on this.
tip 136: Remember that performance reports are not all paper based documents! They can
be wall charts, web pages, pdf files, PowerPoint slide shows, flipchart story boards – anything that
works for their users!
tip 137: Electronic reports, such as pdf or html based reports, enable hyperlinking. And with
hyperlinking you can automate the links between your performance measures to make
cause analysis a little faster. Use the linkages on your measurement map (tip 35:) as the specification
for how to set up the hyperlinks in your reports.
tip 138: If you use the latest in Business Intelligence software to report your measures, you
still need to apply the thinking in the above tips – most BI applications I have seen are more about



flashy things to do with clicking and linking and drilling down, and have very limited capability to
encourage really good cause analysis (see tip 168:) and valid interpretation of information ( see tip
140: to tip 149:). Design a paper-based report first, to get clear how you‟re going to use your
measures and supporting analysis, and you can read more at
www.staceybarr.com/products/reportdesign.html about my how-to kit for designing useful and usable
performance reports, which includes templates of great reports you can use as your starting point.
tip 139: Flowchart your reporting process, linking together all the steps needed to source,
analyse and present the data and measures to their audiences. Define who does what, and when it
needs to happen.



phase 6: interpret what your measures
are saying
Interpreting your performance measures means translating messages
highlighted by performance information into conclusions about what’s
really going on. To turn information into implication, you must discern
which messages are real messages.

The INTERPRET phase of PuMP® is about translating what the numbers are saying
quantitatively, into our everyday verbal language. It‟s a step that the vast majority of decision
makers don‟t even know they are doing, and thus, don‟t do very well. As a consequence, many
decisions have been made which lead to inappropriate or ineffective results.
The topics covered in phase 6 of PuMP® are:
 traditional approaches to interpreting data and their limitations
 more effective approaches to interpreting data and their advantages
 how the interpretation of data is important in assessing if targets have been met or not

know when a difference is really a difference
tip 140: Just because your spreadsheet or charting software can draw a trend line through your
data points, doesn’t always mean there is a real trend there. Often there can be too much
variation to be sure, or another non-linear pattern might better explain the change over time (such as
a step change). If your R2 value (see analyse chapter) is less than 80% (or so), you have to question
how what the trend line really saying to you about performance.
tip 141: “Understanding variation” is a very important (no, essential) skill in interpreting
performance measures. And it doesn‟t mean using statistics like “percent variation from budget”
either. Find out about Donald Wheeler [ref 30] and his book “Understanding Variation: the key to
managing chaos” to discover why this is so important and what it really means.
tip 142: Beware of rolling averages or moving averages. They were really designed to
smooth variation (such as seasonal variation) out of a time series. But because they mask this
variation, you simply can‟t tell if a real change has occurred (until much later) or when it actually
occurred. Looking at overall long term trends doesn‟t help us respond when we need to in order to
keep performance tracking in the direction we need.
tip 143: In her book “Leadership and the New Science” [ref 16], Margaret Wheatley has a chapter
called “The Creative Energy of the Universe – Information”. In this chapter, she addresses the issue
of interpretation of data from a very non-measurement and non-statistical perspective. She mentions
that “the greater the ability to process information, the greater the level of intelligence” that the
organisation will have. Valid interpretation of measures is vitally important since it is an essential part
of the ability to process information. Valid interpretation is an essential condition for
organisational intelligence.
tip 144: What do you do if users are reacting to individual points of data instead of
looking for real trends and real changes in performance? Ask them how do they know that last



month (or the same month last year, or last year, or whatever the benchmark they are comparing
against) was typical, and thus a reliable benchmark?
your performance measure values, then if you see seven or more points in a row (or 12 out of 14 in a
row) above the mean line, or seven or more points in a row (or 12 out of 14 in a row) below the mean
line, you have a signal that performance has suddenly shifted! Calculate a new mean line
from the series of points that you found on the one side of the mean line. That‟s your new overall
level of performance. Don‟t recalculate this new mean line until you see another signal.
your performance measure values, then if you see seven or more points in a row (or 12 out of 14 in a
row) consecutively increasing or consecutively decreasing, you have a signal that performance
has gradually shifted! Calculate a new mean line from the first seven points you get AFTER the
series of points that you found consecutively increasing or decreasing. That‟s your new overall level
of performance. Don‟t recalculate this new mean line until you see another signal.
tip 147: If you have implemented tip 98: where you added control limit lines to the time series chart
of your performance measure values (that is, you have a proper statistical process control chart),
then if you see a point fall outside the control limit lines, you have a signal that an abnormal
event occurred. This is not indicative of any change in performance, just the result of a single
event having a temporary effect.
tip 148: If you have implemented tip 98: where you added control limit lines to the time series chart
of your performance measure values (that is, you have a proper statistical process control chart),
then if you see several or many points fall outside the control limit lines, you have a signal that
performance is chaotic. This is indicative of lack of control or stability in the process or system
that produces your performance result..
tip 149: Survey results are used by many, many organisations, but they are often not used
properly. Do you know what a confidence interval is and how to use it? Effectively it tells
you how reliable the survey result is that it relates to. As one example, imagine that employee
satisfaction this year is 4.5 and last year it was 4.0, giving a difference of 0.5 (an improvement). This
difference of 0.5 would have a confidence interval, and just say it‟s 95% confidence interval was 0.5 
0.6 which is represented as [-0.1,1.1]. While 0.5 looks like a nice improvement, there‟s a 95% chance
that there was no improvement at all, since the confidence interval contains zero in its range.

assess if you are on target (or not)
tip 150: Knowing whether or not your performance has met a target or not is really about
knowing whether the process or system that produces that performance result is capable of
continuing to produce that result. Don‟t rely on a comparison of year-to-date with an annual target, or
last month with a monthly target to decide if your system or process is capable. Remember that
variation is the key to understanding changes in performance (see tip 141:).
tip 151: If you use statistical process control charts (see tip 96:) then decide what exactly you
should be comparing with your target. If your target is to improve the average level of
performance, then use the mean line, or if your target is to set a maximum level, then use the upper
control limit, or if your target is to set a minimum level, then use the lower control limit, or if your target
is for a range, then use both the control limits.
tip 152: Don‟t forget to keep monitoring performance even after the target has been
met – make sure the improvement you implemented to reach the target is sustainable before taking
the measure off your radar.



phase 7: apply your measures to
improve performance
When you have worked out what is really going on with your
organisation’s performance, you are ready to make some decisions
about what to improve, how much to improve it by and how to do that
improving.

We all know that performance measurement for measurement‟s sake is a waste of time and
effort. Putting performance measures to use to improve the business is what phase 7 of
PuMP®, APPLY, is all about. How to get from interpretation to action.
The APPLY phase of PuMP® covers topics such as:
 the role of measures in decision making, plan review and improvement
 root cause analysis
 setting performance targets

Page 34 of 46 http://www.staceybarr.com


use measures to review your plans
tip 153: If your performance measures were selected in line with your business plans (see phase
1:), then your measures are an indication of the degree to which you have achieved your plan. It
might, therefore, be useful to refer to your business plans when you are reviewing your
performance measures.
tip 154: When you report performance measures (see the tips for tip 103:), also report
information about improvement actions that are being taken in response to the signals (see
the tips for phase 6:) those measures have given.
tip 155: Organisational learning is a process that permeates every business activity, and that
includes performance management. Learning happens when you check to see if your
decisions and improvement actions worked. In other words, as a result of your decisions and
improvement actions, did your performance measures achieve their targets without any unintended
consequences?
tip 156: Do your measures indicate that you achieved your business plan? If so, then you may
now be ready to review your business plan and also your selection of performance
measures. But don‟t forget to ensure the improvements you made are now “business as usual” and
not temporary.
tip 157: One very important application of performance measures is in regular plan
review. Strategic performance measures should be used by senior managers to regularly review
progress of performance relative to strategic goals. Likewise for tactical and operational goals.
Performance measures are the feedback loop between the planning process and the improvement
process – to help us monitor the gaps between “as is” performance and “should be” performance.

be clear about the role of measures in decision making
tip 158: One of the most basic capabilities any decision making team will need to effectively use
performance measures is the skill of dialogue [ref 8]. Dialogue is not just talking, it‟s engaging in a
process of balanced listening, enquiry, observation and reflection that results in deeper
understanding, expanded mental models and more possibilities.
tip 159: Do you know who to hold accountable for performance results? This usually
means that if a performance measure is trending in the wrong direction, or not achieving target, a
particular person is dragged over the coals or „given the sack‟. Businesses are getting more and
more complex and as a consequence, performance results are being influence by so many different
things. NO ONE person should ever be held accountable for performance results. See tip 160:.
tip 160: When it comes to performance measurement and management, the ideas things to
hold people accountable for include regularly monitoring the performance measure, validly
interpreting the measure‟s results, identifying root causes, initiating improvement actions, evaluating if
those improvement actions worked, and learning from the evaluation on the organisation‟s behalf.
tip 161: The decision making process that uses performance measures has distinct
steps, which include: prioritising which results to respond to, describing the desired outcome or
results to achieve, understanding the current capability of the system producing the outcome,
exploring any unintended consequences of taking action, developing strategies, implementing the
strategies and finally, checking if it all worked.
tip 162: Benchmarking with other organisations (either in your industry or not) is a great
way to share learnings and gather ideas for improvement. Go ahead and compare your performance
measure results but be aware that they may define their measures differently, be operating in a
different context and put a different priority on their measures. Focus more on dialogue and sharing
ideas about improvement.



tip 163: When you sit down to review your performance measures, and you identify a list of
improvement opportunities, how do prioritise them? Or do you try to do them all? To borrow from
Stephen Covey [ref 22], which are the big stones and which are the pebbles?
tip 164: Before you decide on any improvement activities, you will save heaps of time and drama if
you clearly define the results you want to create first. Use sensory-based language [ref 14]to
paint a verbal picture of the outcomes you want as a result of improvement activity.
tip 165: Newton‟s Third Law states that for every action, there is an equal and opposite reaction. If
you make a change to your business to improve it, where is the reaction going to come from?
Is it a reaction you want or one you don‟t want? Is it a reaction you can manage, or one better
avoided? How can you improve performance in a way that minimises the inevitable unintended
consequences?
tip 166: Unless your organisation checks to see if decisions made and actions taken have the
desired effect on performance, your organisation will miss out on creating some very valuable
knowledge about its own performance dynamics. Often the root causes of one performance
area are the same root causes of other areas – if you find out how to fix them, this knowledge can be
used elsewhere.

make improvement stick by fixing root causes
tip 167: If you want to find performance improvements that stick, then you will need to do
some root cause analysis. This means thinking beneath the symptoms of poor performance that are
so obvious, and digging down until you find the fundamental causes of these symptoms. Try using
Peter Senge‟s “the five whys” technique [ref 7]: keep asking “why” until to find the action that, if
changed or corrected, will prevent the symptoms from returning.
tip 168: Drawing causal loop diagrams is also a useful strategy for understanding the
dynamics producing a particular (unwanted) symptoms. These diagrams consist of loops that show
the causal relationships between various results or outcomes which collectively produce the
symptoms your performance measure might be showing you. Pegasus Communication‟s website is
a great resource for tools like this, so visit www.pegasuscom.com/cld.html to find out how to draw
causal loop diagrams.
tip 169: Process mapping and analysis is a great way to understand the factors limiting the
current capability of the system creating your performance results. It helps greatly to define the
system you intend to improve, before you try to improve it. Just type in “process mapping and
analysis” in your web browser and go prospecting for resources!
tip 170: If you use statistical process control charts, then the current range indicated by the upper
and lower control limits (the „voice of the process‟ or „limits of natural variation‟) compared to your
target range is an indicator of your system’s current capability. If the current control limits
are within the target range, your system is capable, but if the current control limits are wider than the
target range, your system is not capable. Unless something changes, you will continue to get
performance results that randomly vary within your current control limits – and thus some will fall
outside your target limits. You will know when capability has changed when these control limits
change.
tip 171: Always develop a range of improvement options and evaluate their feasibility
without judgement before making the final choice for what improvement actions to implement. Start
wide, then get narrow. It‟s much harder to start narrow, then get wider when you discover your
solution ideas just won‟t cut it.
tip 172: There are many improvement methodologies available, and one in particular has proven
itself: six sigma. Made famous my Motorola, six sigma is a very structured and disciplined
method of improvement which requires a very dedicated champion. Not for the light hearted.
More for those serious about real improvement.



tip 173: If you involve the people who work in the process or area that you want to
improve when you are designing improvement solutions (or get them to do it themselves), you will
get more ownership of the change. People hate having things done to them, we all like to be
consulted and even better, involved.
tip 174: After deciding to implement a particular improvement action in response to a performance
measure signal, you may like to go back to phase 1 of the performance measurement process
(select) and develop one or two new measures to provide regular feedback about how your
improvement actions or strategies are going.

the most useful targets don’t come out of thin air
tip 175: Before you set a target for a performance measure, first identify what the root
causes are that are holding performance at the unacceptable level and evaluate the resources you
have available to manage these root causes. What amount of change can you afford? What amount
of improvement can you achieve with that investment? Using this as your starting point for the target
means everyone will be able to see it is possible to reach it and be more motivated.
tip 176: Benchmarking is a useful source of information that can help you set targets for
your performance measures. What is industry or world‟s best practice for the process or result you
want to set the target for? Does it make sense in the context of your industry or organisation?
tip 177: Never set a target without being able to describe how the target will be able to be
reached by the people responsible for reaching it. What strategies will increase current capability to
the desired level of capability? How will these strategies be implemented and resourced?
tip 178: Remember that target setting has the risk of driving behaviour toward achieving
the target (funny, that). So make sure that achieving the target is only going to be good for your
organisation and not cause significant unintended consequences.
tip 179: When you are setting a target, involve the people that will participate in achieving
it. When we help create something, we care about it more.
tip 180: If you are writing goal or objective statements, a good recipe is:
the direction + the measure (optional: + the current level) + the target + timeframe. For example,
decrease average debt recovery cycle time (from 69 days) to 29 days by June 2005.
tip 181: There is no reason to set a single, large-step target for your measures. It can often be
more motivating if you set a series of staged targets that give you more manageable milestones
to achieve which collectively work up to the ultimate target. For example, you might look for a
reduction in average debt recovery cycle time of 5 days in the next 3 months, working up to a 10
days after 6 months, and then 40 days by 12 months.


202 tips to measure performance

202 tips to measure performance

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202 tips to measure performance