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HR
ANALYTICS
PRESENTED BY AMENDA JOY
LAMP Frame work
– We believe that a paradigm extension toward a talent decision science is key to
getting to the other side of the wall. Incremental improvements in the
traditional measurement approaches will not address the challenges. HR
measurement can move beyond the wall using what we call the LAMP model
Lamp Framework
– L Logic
– A Analytics
– M Measure
– P Process
Logic
Without proper logic, it is impossible to know where to look for insights. The logic element of any
measurement system provides the "story" behind the connections between the numbers and the effects
and outcomes. In this book, we provide logical models that help to organize the measurements and show
how they inform better decisions.
Analytics: Finding Answers in the Data
Even a very rigorous logic with good measures can flounder if the analysis is incorrect. For example, some
theories suggest that employees with positive attitudes convey those attitudes to customers, who, in
turn, have more positive experiences and purchase more. Suppose an organization has data showing that
customer attitudes and purchases are higher in locations with better employee attitudes.
Analytics is about drawing the right conclusions from data. It includes statistics
and research design, and it then goes beyond them to include skill in identifying and articulating key
issues, gathering and using appropriate data within and outside the HR function, setting the appropriate
balance between statistical rigor and practical relevance, and building analytical competencies
throughout the organization. Analytics transforms HR logic and measures into rigorous, relevant insights.
Measures: Getting the Numbers Right
The measures part of the LAMP model has received the greatest attention in HR. As discussed in
subsequent chapters, virtually every area of HR has many different measures. Much time and attention is
paid to enhancing the quality of HR measures, based on criteria such as timeliness, completeness,
reliability, and consistency. These are certainly important standards, but lacking a context, they can be
pursued well beyond their optimum levels, or they can be applied to areas where they have little
consequence.
Precision is not a panacea. There are many ways to make HR measures more reliable and
precise. Focusing only on measurement quality can produce a brighter light shining where the keys are not!
Measures require investment, which should be directed where it has the greatest return, not just where
improvement is most feasible.
Process: Making Insights Motivating and
Actionable
The final element of the LAMP framework is process. Measurement affects decisions and behaviors, and
those occur within a complex web of social structures, knowledge frameworks, and organizational cultural
norms. Therefore, effective measurement systems must fit within a change-management process that
reflects principles of learning and knowledge transfer. HR measures and the logic that supports them are part
of an influence process.
The initial step in effective measurement is to get managers to accept that HR analysis is possible and
informative. The way to make that happen is not necessarily to present the most sophisticated analysis. The
best approach may be to present relatively simple measures and analyses that match the mental models that
managers already use. Calculating turnover costs can reveal millions of dollars that can be saved with
turnover reductions,
Conclusion
The letters in LAMP stand for logic, analytics, measures, and process, four critical components of a
measurement system that drives strategic change and organizational effectiveness. Measures represent
only one component of this system. Although they are essential, without the other three components, the
measures and data are destined to remain isolated from the true purpose of HR measurement systems.
The paradox is that genuine insights about human resources often exist in the areas where
there are no standard accounting measures. The significant growth in HR outsourcing, where efficiency is
often the primary value proposition and IT technology is the primary tool, has exacerbated these
issues.7 Even imperfect measures aimed at the right areas may be more illuminating than very elegant
measures aimed in the wrong places.
Thank You

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Hr analytics

  • 2. LAMP Frame work – We believe that a paradigm extension toward a talent decision science is key to getting to the other side of the wall. Incremental improvements in the traditional measurement approaches will not address the challenges. HR measurement can move beyond the wall using what we call the LAMP model
  • 3. Lamp Framework – L Logic – A Analytics – M Measure – P Process
  • 4. Logic Without proper logic, it is impossible to know where to look for insights. The logic element of any measurement system provides the "story" behind the connections between the numbers and the effects and outcomes. In this book, we provide logical models that help to organize the measurements and show how they inform better decisions.
  • 5. Analytics: Finding Answers in the Data Even a very rigorous logic with good measures can flounder if the analysis is incorrect. For example, some theories suggest that employees with positive attitudes convey those attitudes to customers, who, in turn, have more positive experiences and purchase more. Suppose an organization has data showing that customer attitudes and purchases are higher in locations with better employee attitudes. Analytics is about drawing the right conclusions from data. It includes statistics and research design, and it then goes beyond them to include skill in identifying and articulating key issues, gathering and using appropriate data within and outside the HR function, setting the appropriate balance between statistical rigor and practical relevance, and building analytical competencies throughout the organization. Analytics transforms HR logic and measures into rigorous, relevant insights.
  • 6. Measures: Getting the Numbers Right The measures part of the LAMP model has received the greatest attention in HR. As discussed in subsequent chapters, virtually every area of HR has many different measures. Much time and attention is paid to enhancing the quality of HR measures, based on criteria such as timeliness, completeness, reliability, and consistency. These are certainly important standards, but lacking a context, they can be pursued well beyond their optimum levels, or they can be applied to areas where they have little consequence. Precision is not a panacea. There are many ways to make HR measures more reliable and precise. Focusing only on measurement quality can produce a brighter light shining where the keys are not! Measures require investment, which should be directed where it has the greatest return, not just where improvement is most feasible.
  • 7. Process: Making Insights Motivating and Actionable The final element of the LAMP framework is process. Measurement affects decisions and behaviors, and those occur within a complex web of social structures, knowledge frameworks, and organizational cultural norms. Therefore, effective measurement systems must fit within a change-management process that reflects principles of learning and knowledge transfer. HR measures and the logic that supports them are part of an influence process. The initial step in effective measurement is to get managers to accept that HR analysis is possible and informative. The way to make that happen is not necessarily to present the most sophisticated analysis. The best approach may be to present relatively simple measures and analyses that match the mental models that managers already use. Calculating turnover costs can reveal millions of dollars that can be saved with turnover reductions,
  • 8. Conclusion The letters in LAMP stand for logic, analytics, measures, and process, four critical components of a measurement system that drives strategic change and organizational effectiveness. Measures represent only one component of this system. Although they are essential, without the other three components, the measures and data are destined to remain isolated from the true purpose of HR measurement systems. The paradox is that genuine insights about human resources often exist in the areas where there are no standard accounting measures. The significant growth in HR outsourcing, where efficiency is often the primary value proposition and IT technology is the primary tool, has exacerbated these issues.7 Even imperfect measures aimed at the right areas may be more illuminating than very elegant measures aimed in the wrong places.