Are you tracking sand strokes or sand saves?
In order to get the most out of Big Data and AI corporations must implement and nurture a data-driven corporate culture. Creating that culture takes time and abundant leadership to establish, nurture, embrace and grow. Becoming data driven is not just an issue of spending money in analytics software and graphical displays, it is a thoughtful, immersive and iterative process that depends on trusting the data. So how do we get to do that; trust?
As part of my blog series on how to “Transform Your Corporate Culture to Best Use Big Data”, here are three suggestions on how to develop trust in corporate data by defining and selecting the right KPIs for the organization. In my previous blog we discussed normalizing corporate data to collect facts in an optimal form, and to define KPIs mathematically. Let’s now look at how KPIs should be selected and presented to the organization to get optimal management results.
I was recently part of a WebEx call that allowed me to see the configuration of a partner’s salesforce (SFDC) CRM system. While the fact that they were using SFDC in “classic” mode first grabbed my attention, it was the “what” and “how” they were serving the data to their users.
1. KEEP THE AUDIENCE IN MIND
Finance types love spreadsheet formats and charts that show month-to-month or year-to-year trends. Operations types prefer flow formats that show progression trends in a continuous form. Sales types like dials that show values now. Not yesterday, not even “today”; now. If you have normalized corporate data and then define your KPIs mathematically, the above behavior will not be an issue because today’s tools allow you to present the same KPI in different manifestations.
Give the Finance types spreadsheets, Sales Ops funnel charts, and the Sales team additional sales quota. I mean, give the Sales team dial views. For that matter, let anyone in the organization consume the data and KPIs in the way that best works for the individual. This means that those in charge of presenting the data to the users must have an open mind and plan how to collect the data so that they can serve it for consumption as desired.
There is nothing funnier than watching a Sales Director looking at the underlying detail of a PNL statement on the SFDC screen and having the CFO ask him/her about the profitability of the deals being sold by the team. The data is there, but getting to the answer is a bit of a circus; and it need not be one.
2. DEFINE KPIs MATHEMATICALLY AND ALSO VERBALLY
It is paramount to define KPIs with mathematical formulas so that given data, the results are always the same. It is imperative that you develop a “decoder ring” in written form so that everyone looking at the KPIs, regardless of form, can come to the same actionable conclusions. If you forego the latter definition, you run the risk of having two or three leaders in a meeting look at the same spreadsheet, chart, or dial in a dashboard, and come up with a completely different and competing course of action. This is antithetical to the fundamental purpose of KPIs.
For those that are itching to say that “one chart may have many interpretations” – you are right. Take the time not only to define KPIs verbally, but also to establish consensus in their verbal definitions and interpretations so that you have the teams coalesce in their interpretations and following actions. This requires work a priori and constant re-evaluation. It requires dialogue and healthy challenge when new voices present a different interpretation.
It’s humorous to see a running-total daily sales chart for the month in a meeting, see an “up and to the right” surge and hear a voice say “we are selling more” - (thank you Holmes). The real question is “Why are we selling more?” In order to answer that question, you need clear definition of the factors that go into the KPI and drive changes. If you do this, you will know the levers you need to pull and when to do so to make sure you get the desired results.
3. AGREE ON THE LEVERS THAT IMPACT THE KPIs
Recall that you should start with your strategic plan and corporate goals in mind, and then identify the Key Performance Indicators (KPIs) that will provide the factual basis to direct corporate decisions and validate failure or success calls. As the KPIs are identified and then defined, it is ever so important to also understand their interpretation and the factors or “levers” that control their behavior.
This is useful to all hands, but specially to those rising stars that you are coaching to assume greater responsibilities. The levers of the corporation are not obvious to all, junior or senior, and they should be uniformly defined and used in order to achieve consistency. If the levers are well defined, authority may be more easily delegated and action taken at the right level and time.
This is not to say that anyone has the authority to pull on any one lever; but that everyone should know which lever to recommend pushing or pulling.
And a final thought – Don’t be cavalier about your selection and use of KPIs
Again, be thoughtful on what KPIs you select. Don’t just “copy/paste” and use the basic KPIs that came with your BI tool like “on time delivery”. Be mindful of the effects of KPIs in your teams. If you select as a KPI the “number of bids put out in a quarter” or “the number of opportunities abandoned in a quarter” you may inadvertently be sending the wrong message to your Sales team. Neither of them addresses the quality or efficiency of the team’s work. Harping on these may force behaviors the corporation does not want.
If you golf, you may count “sand strokes”. I’d rather count “sand saves” as the latter not only can tell me how many times I ended up “in the beach”; but more so the quality of my effort in recovering and saving birdie or par.
Be purposeful. If you are going to collect data, learn from it and work on improving your KPIs every day. That is one of the key elements of attaining a data-driven corporate culture.
////////////////
As a reminder, I recommend that you read the following Harvard Business Review (HBR) articles and NewVantage Partners’ survey. Good stuff for sure and they will certainly help “normalize” the data as you read these blogs.