The 10 necessary steps to convert your raw data into KPI wisdom.
Famous astronomer Clifford Stoll says “Our networks are awash in data. A little of it is information. A smidgeon of it shows up as knowledge. Combined with ideas, some of that is useful. Mix in experience, context, compassion, discipline, humor, tolerance and humility and perhaps knowledge becomes wisdom.”
Data is just data. Making your performance measurement data have meaning and produce insights, requires skilled people, who care about improvement, working together in teams using a rigorous approach. Otherwise, people avoid the measures, and our efforts are wasted. Watch this short video: Why we never do measurement alone
Ready for better insights from your KPI’s data? Take these 10 Steps.
STEP 1: What is the intent of this measure?
- Do we understand why this measure matters and what we are trying to know or improve? Is it connected to something strategically important within our organization?
- Tip: If you can’t answer these “so what” questions above, then stop reporting on this specific measure and see if anyone notices. If you can answer them, then move to Step 2.
STEP 2: Where does this measure fit?
- Do we understand the relationships this measure has to other related processes or outcomes in our organization? (which will allow us to detect any intended or unintended consequences from driving improvement with this measure).
- Tip: The PuMP results map is a very powerful conversation tool to unearth these relationships. Learn more about the results map
STEP 3: How do we calculate the data points?
- Do we know the formula’s precise statistical equation to consistently create the data values we use in our interpretations of performance over time?
- Tip: Ensure the formula is specific enough for analysts to bring the measure to life the same way every time. Create an internal system that allows anyone to look up that measure’s formula to see how the data points are calculated.
STEP 4: How frequently can we get our data values?
- Do we know the timeframe over which the measure’s values will be based, such as daily, weekly, monthly?
- Tip: Choose a frequency that enables the team to see and interpret natural variations in the measures’ data we are tracking. The frequency must be often enough so we can change course if needed.
STEP 5: What is the scope of this measure?
- Do we know the boundaries that define the subset of data?
- Tip: Document in writing what is included and what’s not (for example is every customer included in a satisfaction survey, or only those who made a purchase)? Document when it begins and when it ends (for example, where the cycle time consistently starts and stops).
STEP 6: Where are we getting the data items from?
- Do we know the source fields that provide the information needed for the measure’s formula?
- Tip: Apply explanatory information such as data names to avoid confusion, a data item description, source system, sourcing/collection process, availability, integrity, and the data owners’ names.
STEP 7: What visualization chart is best for seeing change in our strategic performance?
- Do we know which charts to use when, to help us turn our quality data into useful insights (wisdom) about whether we are closing our strategic performance gap over time? Do we understand why performance measures need “trend-over time” comparisons that compare the average historical performance of the data vs the desired future performance (often called a target). Are we clear why comparing only 2 points of data does not reveal statistically accurate changes in performance?
- Tip: If you are not familiar with XMR charts, now would be a good time to explore how this line chart (with an extra level of statistical calculation added) is best for providing teams with wisdom during strategy execution. Learn about XMR charts
STEP 8: What frequency is best for reporting?
- Do we know how often we need to report the information of what the visualized data is telling us (insights) to users? Sometimes it is the same as the calculation frequency and sometimes it may be different.
- Tip: Frequency could be daily, weekly, monthly or quarterly, but annually is NEVER frequently enough if we need to make decisions that impact the achievement of important outcomes/results.
STEP 9: When do we take action and when don’t we?
- Do we know when we should be responding to variations in our data and when we shouldn’t respond? We want to avoid knee-jerk reactions to random changes, but we also don’t want to miss important signals that provide predictive insights.
- Tip: Make sure the actions we take are not in reaction to statistically invalid trends or comparisons (such as this month compared to last month or same time next year).
STEP 10: Who is responsible for improving the performance of this outcome/result?
- Do we know who is monitoring this measure and how often, so we can learn from the insights? Does the person have the authority to make decisions about what to do next if performance is not improving?
- Tip: Having a person responsible for closing the performance gap can be different from the person who is maintaining the integrity of the data.
Taking these 10 steps will skyrocket the quality of your KPI insights for decision making, but remember that most organizations have poor “measurement literacy”, allowing human emotions and naïve intuition to get in the way of truly wise decision-making.
However, it is never too late to invest in improving your organization’s process of converting data to information, information to knowledge, knowledge to wisdom, and finally wisdom to improved organizational performance!
(Special thanks goes to Dean R. Spitzer, PhD, Author of Transforming Performance Measurement, 2007 for his generosity of knowledge and thought within the measurement space and with his permissions with Adura Strategy Inc.) Thanks also to Stacey Barr, the Founder and Creator of the PuMP® Performance Measurement Process and the Evidence-Based Leadership program.
Louise Watson, Adura Strategy Inc. is licensed by Stacey Barr as the Partner for North America for training and consulting.
