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Making HR Count

In the age of big data, it has become mandatory for strategic HR professionals to have strong qualiitative skills. The following presentation conducted in 2004, predicted this shift and outlined why and how HR can stay ahead of the data revolution.

In the age of big data, it has become mandatory for strategic HR professionals to have strong qualiitative skills. The following presentation conducted in 2004, predicted this shift and outlined why and how HR can stay ahead of the data revolution.

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Making HR Count

  1. 1. Making HR Count OPRA Consulting Group Excellence in Business. Excellence in People.
  2. 2. Overview • HR and Statistics - an open discussion • Why have metrics stayed out of the hands of HR folk? • Hr Metrics: The myths and legends • What makes a good metric? • Who has a vested interest in HR metrics? • Demonstration • Descriptive statistics • Simple inferential statistics • Survey design • Classification modelling and prediction • Building a positive metrics-based culture
  3. 3. HR and Statistics: Discussion • Who currently uses statistics in their day-to-day HR work? • Who currently completes their own statistical analysis to support HR activity? • Whose blood turns cold when their hear the word “Statistics?”
  4. 4. HR and Statistics: Discussion • Who thinks that they would be more convincing if they were able to use statistics in their business? • Who thinks that they would secure more $$ for HR activity if they could show that HR activity was returning a value to the business? • Who would like to be more proficient with statistics as an HR professional?
  5. 5. HR CONTINUES TO EVOLVE
  6. 6. Textbook Definition Metrics are a system of parameters or ways of quantitative assessment of a process that is to be measured, along with the processes to carry out such measurement. Metrics define what is to be measured. Metrics are usually specialized by the subject area, in which case they are valid only within certain domain and cannot be directly benchmarked or interpreted outside it. Generic metrics, however, can be aggregated across subject areas or business units of an enterprise.
  7. 7. The Business Case “Without HR metrics, no one in management can really put a finger on what's working or not working with the people who make up an organisation. HR's success at measuring "people issues" directly contributes to informed decision-making by executives and board members. The challenge for HR is to measure and deliver meaningful data that is relevant to the bottom line”. (C. Johnson: HR Metrics: The Business Case)
  8. 8. And……. “The future for metrics is now. Our need to measure and to apply measurement to strategic analysis and strategic decision-making increases every day. HR metrics are not simply equations to think about applying in the future when you presumably will have more time; they should be commonplace for every organization, regardless of size, industry; location or success. By showing the value of assets or the return on investment, HR metrics become key to advancing the HR profession”. (HR Metrics: A must, D Cohen)
  9. 9. And Again..…. “In a highly competitive world dominated by CFOs who want to cut your budget, it is no longer optional to demonstrate your value. Everyone is accountable! It's interesting that when people ask me how you can differentiate between world class and average HR departments, the one factor that stands out dramatically is the extensive use of metrics (or lack thereof) to measure HR success. The very best — like Intel, Cisco and Microsoft — are metrics fanatics, while the worst use costs, feelings, and instincts to judge their success. (Dr John Sullivan, 2003, “Why Metrics are Essential”)
  10. 10. Why have metrics stayed out of the hands of HR professionals?
  11. 11. MYTH VS REALITY
  12. 12. Myth: Metrics are difficult Reality: • As more departments become paperless the ability to sort data becomes easier with ‘point and click’ solutions • Most metric calculations can be done on an excel spreadsheet or with existing software • The best metrics are self explanatory and can be easily defined with a simple description
  13. 13. Myth: Collecting Data is Expensive Reality: • Over-collecting of data is common. Whenever possible, use existing information • You do not have to measure every event or job. • Instead prioritize jobs, and business units and use sampling techniques to reduce the time and costs • Robust software to support the collation of metrics is available for $2,000 (per licence)
  14. 14. Myth: Our Organisation isn’t ready for this Reality: • Good metrics measure the things that senior managers care about • Build credibility by pre-testing your proposed metrics with say, the CFO to ensure they are robust • In tough economic times, you prove your business impact or you are gone
  15. 15. Myth: HR Metrics takes too much time Reality: • Once you get meaningful data (the hard bit!), running the metrics is easy • Work with other business units to build an evaluative environment • Once the systems are in place the time required to generate metrics is very short
  16. 16. Myth: HR Metrics is too difficult Reality: • Once you get meaningful data (the hard bit!), running the metrics is easy • Work with other business units to build an evaluative environment • Once the systems are in place the time to complete metrics is very short
  17. 17. Who has the vested interest in HR metrics?
  18. 18. Who has the vested interest in HR metrics? • Consulting firms use metrics as their “Commercial” advantage……the less you know the more advantage they have. • They then on-sell YOUR metrics as “benchmarking data”, for their own commercial gain.
  19. 19. Who has the vested interest in HR metrics? • Where possible, organisations should aim to move towards greater self- sufficiency. • You have the vested interest because it is your organisation.
  20. 20. Why Would I Use HR Metrics? As a HR professional, you should use metrics if you: • Don’t want to be over-taken by a new breed of HR professionals • Want to demonstrate H.R’s value to the organisation • Want to become an invaluable strategic player in your organisation • Want to anticipate organisational change, not just follow it
  21. 21. What is a Good Metric? • Aligned with business: 62% of Fortune 500 companies cited "to better align HR strategy with corporate strategy" as the number one goal for HR, but one of the most difficult to achieve. Good metrics can bridge the gap. • Actionable and predictive: A good metric must provide information that can be acted upon. Too often, HR measures for the sake of measuring, without really thinking “what do I do with this? • Consistent: A good metric is consistent in what it measures, otherwise, the value of its comparison is useless. • Time-trackable: A good metric must be able to be tracked over time. It is not a snapshot of an activity at one moment in time.
  22. 22. Internal Research Design Identify solution Analyse data Identify data to collect Identify statistics to help solve research question Identify research question Identify a problem
  23. 23. How long would you spend looking for a new intranet system worth NZ$30,000?
  24. 24. Return on Investment Does using assessments in selection save $$ ? • Incremental costs with inaccurate selection • Small employers = savings of US$18m per year large employers = savings up to US$16b per year (Schmidt & Hunter, 1981) • Higher aptitude = easier to train • “Performance managing out” can be difficult
  25. 25. Hidden costs associated with poor selection decisions • Often, we can only recognise poor performers after they have made mistakes • If a performance issue: Training and associated costs, but not always a guaranteed solution • If there are attitudinal problems, these cannot be trained
  26. 26. • Poor performers under NZ law, stuck with individual for 3 months (minimum) or more likely 6 months • Poor performers  wages/salary • Poor performers  mistakes Hidden costs associated with poor selection decisions
  27. 27. • Personal grievances for unjust dismissal • $25,000 to $60,000 in court costs only • $25,000 to $60,000 additional if company loses • Top executives tied up in mediations for hours – lost revenue Hidden costs associated with poor selection decisions
  28. 28. Cost Modelling But do assessment tests actually “add value”? Utility (U) - the “added valued” of using personality (or other assessment) measures U = N * T * r (x y) * $ S d (y) * Z (x) – c N = number of candidates selected T = expected average tenure of those selected r(x y) = correlation between predictor score (x) and $ value pay off (y) $Sd(y) = standard deviation of $ pay off for selected applicants i.e. $ profit difference Z(x) = average standard predictor score for the group C = total costs of selection for all applicants
  29. 29. Building a Positive Metrics Based Culture Keep it Simple • If a metric is not self explanatory, or can't easily be defined with a simple description, then it is probably too complex. Only Track Metrics you Intend to Use • Consider those that relate in particular to such things as performance, continuous improvement and responsiveness. Keep Metric Goals Realistic • Set realistic quarterly goals so the organisation can see results.
  30. 30. Building a Positive Metrics Based Culture Keep your Metrics Visible Post all your key vital metrics in a highly visible place. Colourful trend charts might show: • The metric • Your goal • The industry benchmark • Your current performance Celebrate Metrics Metrics get a bad rap because we typically use them to show all the things we need to improve. Develop a culture that embraces metrics by using them to demonstrate all the things you are doing right.
  31. 31. -End-

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