Use Business Analytics and Aligned Metrics to Drive Higher Performance

Use Business Analytics and Aligned Metrics to Drive Higher Performance 120219

Mitchell Weisberg  February 19, 2012

Organization leaders and business leaders who are adopting data driven management and metrics driven performance management are achieving significant gains over those organizations that are remaining with traditional methods of management. 

The anecdotal evidence has been mounting since Michael Lewis published the book Moneyball in 2003, and followed by the recent release of the movie starring Brad Pitt.  Now additional hard data from academic sources are now available to verify that these achievements are real and lasting. These academic studies looked at business performance in large samples of industries over a period of time and found statistically significant gains in productivity in those companies using data-driven decision making over traditional management methods.  This mounting evidence makes a compelling argument for all management to migrate in this direction. 

In my practice of Metrics Driven Performance Management I have seen increased performance results in companies as a result of their adopting metrics aligned with strategy, using the balanced scorecard tools and approach over the past 10 years.

Two recent studies provide evidence of the benefits of data driven management, each from a different perspective.  A study by Aaron Crabtree (University of Nebraska) and Gerald DeBusk (University of Tennessee) demonstrated the business value of using performance metrics aligned with the business strategy, and a study by Erik Brynjolfsson, Lorin Hitt, and Heekyung Kim (Massachusetts Institute of Technology) demonstrated the benefits of business decisions based results from mining large databases of organizational information.

The study by Crabtree and DeBusk examined 160 public companies, analyzing measures of organizational value delivered including share price.  They compared balanced scorecard users and nonusers, matched by industry and organization size. Over a three-year period the balanced scorecard users outperformed the nonusers across three key performance measures by an average of 28%.  They concluded that "the balanced scorecard is an effective strategic management tool that leads to improved shareholder returns." 

 The study by Brynjolfsson, Hitt, and Kim examined 179 large publicly traded firms over a period of 3 years and concluded that the firms that adopted data driven decision-making had output and productivity that was 5-6% higher than what would be expected given their other investments and information technology usage. The data these firms used to support the decision-making was from large data sets of their own marketing, operations and processes. The firms using data driven decision-making  also had greater performance as measured by other performance measures such as asset utilization, return on equity and market value.

These studies support my statement that management should increase their use of data driven decisions in driving their organization’s performance.  They should be using metrics that align with their strategy to ensure that these data-driven decisions are delivering the increase in performance in support of the organization’s goals, rather than just increased performance across the operations.  

Sources:

1.      Erik Brynjolfsson, Lorin Hitt, Heekyung Kim, "Strength in Numbers: How Does Data-Driven Decision Making Affect Firm Performance?", April, 2011

2.      Steve Lohr, “The Age of Big Data”, New York Times, Sunday Review, February 11, 2012.  http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html 

3.      Crabtree and G. DeBusk, “The Effects of Adopting the Balanced Scorecard on Shareholder Returns,” Advances in Accounting, incorporating Advances in International Accounting 24(2008):8-15
     
       Jacques Bughin, John Livingston, and Sam Marwah, "Seizing the potential of ‘big data’" McKinsey Quarterly, OCTOBER 2011,  http://www.mckinseyquarterly.com/Seizing_the_potential_of_big_data_2870