Get the business understanding right! Analytics Teams know that one of their biggest challenges is effective communication and collaboration with their business partners. Projects are plagued with too many iterations to get to a solution, too many detours responding to unfocused requests, and too often the final model results in a positive analytic result that can’t demonstrate business value. What can you do? Analytics and decision modeling expert James Taylor of Decision Management Solutions outlines six questions to ask your business partner before you start modeling and shows you why decision modeling is the best approach to building this shared understanding.

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James Taylor
CEO
Analytics Teams:
6 Questions to Ask Your Business
Partner Before You Model

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James Taylor
Decision Management Solutions
▶ We work with clients to
improve their business by
applying business rules &
analytic technology to
automate & improve decisions.
▶ Vendor-neutral
▶ Original DMN submitter
▶ Using decision modeling since 2011
▶ I have spent the last 14 years
focused on the development of
analytic applications using
Decision Management

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Agenda
▶ Analytic Challenges
▶ Six Questions Frame the Problem
▶ Decision Modeling for Analytics
▶ Decision Models Answer The Six Questions
▶ Wrap Up

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Challenges For Analytics Teams

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Data Science
Insights
Business
Value
There Is A Dangerous Gap In Data Science

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Closing The Gap Delivers Analytic Success
Data Science
Insights
Business
Value
Frame The Problem Build The Model
Plan For
Operationalization

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Challenges Framing Analytics Problems
Too many
iterations
Business
Poor
collaboration with
business and IT
partners
Business value
not the focus
Too many
distractions

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Multiple Perspectives Required
Business

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The Telephone Game
▶ Decision Makers ask for data or an analytic
▶ But this does not help them make the decision
▶ So they ask for more or different data
▶ But that doesn’t help either
▶ So they ask for a different view of the data
▶ …
▶ Until they get fed up and do something in Excel!

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Too Many Distractions
New technology New data New targets

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Demonstrating Business Value
▶ Too many projects focus on analytic accuracy
▶ Need to focus on business value
▶ Teams must connect their analytic to this value

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Six Questions To Frame The Problem
1. How will we measure success?
2. What decisions does the organization make that
have an impact on this measure?
3. What question has to be answered to make a
decision?
4. Who makes these decisions and when?
5. Which decision(s) are we going to change?
6. What are the side effects of changing these
decisions?

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Decision Modeling for Analytics

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Decision Modeling Frames Analytics
▶ Provides “structure” - who, what, how, when
▶ Standardizes approach to decision making
▶ Provides “transparency” of decision approach
▶ Fosters innovation in the business model
▶ Improves/changes the business model
▶ Promotes “buy in”

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Decision Models Frame The Problem
Decision
Input Data
Knowledge
Sources
Sub-
decisions
Analytic
Source: DecisionsFirst Modeler
@jamet123 #decisionmgt

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Decision Models Put Analytics In Context
Process
Decision
Motivation Organization
Department
Team
Role
Role
Team
Department
Organization
Analytic

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Decision Models Answer
The Six Questions

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Six Questions To Frame The Problem
1. How will we measure success?
2. What decisions does the organization make that
have an impact on this measure?
3. What question has to be answered to make a
decision?
4. Who makes these decisions and when?
5. Which decision(s) are we going to change?
6. What are the side effects of changing these
decisions?

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1. How will we measure success?
▶ Objectives of the
sponsors
▶ Measures of success
▶ For instance
▶ Reduce claims in litigation
▶ Improve the loss ratio
▶ Objectives of the
modelers
▶ Measures of accuracy
▶ For instance
▶ Error rate
▶ Lift
Business Measures Not Analytic Ones

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2. What decisions have an impact on this?
▶ Value of data science comes from improved decisions
▶ Any data science project must influence decisions
to add value

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Decision Models Show How To Get The
Impact You Want
Improve
Cross-Sell

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3. What’s the question?
▶ Every Decision in the model has a specific question
▶ What exactly is being decided?
▶ What are the possible answers?
▶ What needs to be known to answer the question?
▶ Data
▶ Answers to other questions
▶ Repeat

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4. Who makes these decisions and when?
▶ Who has to approve the
analytics?
▶ Who has to believe the
analytics?
▶ Who should be kept
informed as the analytic
changes?
▶ Whoever owns the
decision
▶ Those that make the
decision
▶ People who care about
the decision

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See Who Needs To Be Involved or Informed
Risk Management
Retail Operations
Insurance Operations
Customer Service

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5. Which Decision(s) Will Change
Overall
Decision

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Find The Analytics That Work
▶ Ask If Only…
▶ If only we knew if this customer is unhappy
▶ If only we knew if this piece of equipment was going to fail
soon
▶ If only we knew where we were most likely to get a
delivery this afternoon
▶ If only we knew if this provider was ripping us off
▶ …

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6. What are the side effects?
Loan Repayment
Insurance Revenue
Customer Satisfaction

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Six Questions To Frame The Problem
1. How will we measure success?
2. What decisions does the
organization make that have an
impact on this measure?
3. What question has to be
answered to make a decision?
4. Who makes these decisions and
when?
5. Which decision(s) are we going
to change?
6. What are the side effects of
changing these decisions?
▶ Decision models link analytics to
decisions to business metrics
▶ Decisions are defined with
questions and allowed answers
▶ Decision models show who owns,
makes and cares about decisions
▶ Decision models show the specific
structure of a decision
▶ Decision models reveal impact of
changes and analytics

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Getting Started

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Decision
Most Analytic Projects Leave Decisions
In The Dark
Modeling Decisions
Brings Transparency
30©2015 Decision Management Solutions

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Data
Business
Understanding
Data
Understanding
Modeling
Data
Preparation
Evaluation
Deployment
CRISP-DM Phases
1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modeling
5. Evaluation
6. Deployment

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Specific Analytic
Decision
Analytic Models
Overall decision to be
improved
Business Understanding As a Decision Model
Regulations and
Policies
Data

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Decision Modeling For Analytic Projects
▶ Steps
1. Training in decision modeling
2. Establish business value
3. Model effective decision-making
4. Add process, organization, business context
5. Frame and scope the analytic project
▶ Deliverables
▶ Decision Model showing impact of proposed analytic
▶ Analytic, business and IT teams trained & self-sufficient
▶ Best practices and go-forward recommendations
▶ Software, consulting and training

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Decision Modeling for Analytic Projects
▶ Learn more
▶ Download the six
questions brief
▶ bit.ly/6QAnalytics
▶ Ready to start?
▶ Kick off a decision
modeling project today
▶ bit.ly/DMNAnalytics

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Questions?

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Decision Modeling for Analytic Projects
▶ Learn more
▶ Download the six
questions brief
▶ bit.ly/6QAnalytics
▶ Ready to start?
▶ Kick off a decision
modeling project today
▶ bit.ly/DMNAnalytics

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DecisionsFirst Modeler
Collaborative, cloud-based decision modeling software
that puts decisions at the heart of your business
architecture, building better requirements and driving
successful business rules implementations
Key Features
Multi-user, Collaborative
Decision Model and Notation
(DMN) Support
Shared Database, Reusable
components
Automated Consistency and
Completeness Checks
Living Repository

38. Thank You
@jamet123 #decisionmgt © 2016 Decision Management Solutions
For more on
Decision Management, go to:
decisionmanagementsolutions.com
James Taylor
james@decisionmanagementsolutions.com