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SmartData Collective > Data Management > Culture/Leadership > Want to Disprove a CEO’s Wishful Thinking? Use Analytics.
AnalyticsCulture/LeadershipDecision ManagementInside CompaniesPredictive Analytics

Want to Disprove a CEO’s Wishful Thinking? Use Analytics.

GaryCokins
GaryCokins
4 Min Read
Want to Disprove a CEO’s Wishful Thinking? Use Analytics.
Photo by cyberco on Pixabay (https://pixabay.com/photos/digital-marketing-content-strategy-10174516/)
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How often have you heard executives proclaim that next year the target for financial results will be a substantial lift from the current year? For example a CEO may state, “Next year we expect to improve from a 10.3% to 15.4% rate of return on shareholder equity.” Is this leadership or wasted words? Where did the 15.4% come from? How is it substantiated with facts? Is this expectation a goal or a wish?

In my opinion such a high-level aggregate target, typically stated in financial terms, is not a goal – it is a result. That is, highly aggregate targets are a consequence of collectively accomplishing lots of other outcomes. Similar to a track and field pole vault athlete who must have so many things come together to clear the bar – speed, knee lift, arm push-off and body form – an organization must also collectively get it right to optimize the use and strategic alignment of its spending and resources.

But even if an organization can get it collectively get it right, how does the CEO know such a precise financial target – or any target number? The financial return is a dependent variable, not an independent one. That means there can be dozens, arguably hundreds, of interrelated factors, the inherent variables, that can collectively contribute to the financial results. The good news is there is now a way to optimize an organization’s performance.

The heralded solution to aim for maximum financial results is to use strategy maps with a balanced scorecard. Together they serve like a GPS navigation instrument in a car. Although a strategy map and its companion balanced scorecard do not alone provide the power to optimize financial results, when correlation analysis among its KPIs is applied, the maximum achievable return on shareholder equity can be tested and validated. Trade-off analysis can be applied. The amount of spending can be examined to assess when any exceeds a limit that aggregate profits begin to decline.

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A strategy map and its scorecard with KPIs set direction and determine projects and core processes to improve. The underlying power to achieve results comes from the integration of the many enterprise performance management methodologies that I so regularly write about. When the methodologies are integrated and infused with reliable analytics – particularly predictive analytics – then the maximum financial returns can be determined.

Goal or wish? Summary, aggregate enterprise measures are not goals but rather aspired results. The true target setting must shift to project selection and core process improvements – independent variables.

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