Closing the Intelligence Gap - Gary Cokins on Performance Management

This week I attended the 12th annual Balanced Scorecard Collaborative (now called Palladium) Americas Summit conference. This conference attracts relatively more advanced and mature organizations who have implemented strategy maps and the balanced scorecard (BSC) concepts developed by Dr. Robert S. Kaplan and Dr. David P. Norton.

I consider this conference as an early predictor of what “new waves” and emerging trends may progress in the broader Performance Management community. For example, at this conference in 2007 I detected a shift for organizations to pay more attention to strategic projects and initiatives derived from the objectives in their strategy map – and then adequately fund them. This is now better known as StratEx for “strategic expenses” in performance based budgeting.

At this year’s conference I observed three areas receiving increased emphasis and attention to past years.

In Dr. Norton’s opening keynote speech he observed that a barrier slowing the progress in fully adopting the BSC methodology is what he calls “fragmentation.” This is the lack of coordination between and amongst various performance management methodologies (e.g., CRM, Six Sigma quality) and actions. His recommended solution is an “integrated technology platform” with software automation. That is, he viewed that moving from spreadsheets and PowerPoint to commercial BSC software solutions was essential to institutionalize and sustain an organization’s BSC.

The keynote speaker Howard Dresner, a popular IT analyst and business advisor, described the need to create a “performance-driven culture.” He pointed out that at this point in time BSC is well over 15 years old, and its underlying methodologies are proven. (Many of the conference’s case study presentations served as evidence of BSC’s success.) The barrier holding back progress with the vast majority of organizations is cultural including resistance to change and the absence of a “visionary leader.” Howard has developed a survey diagnostic that organizations can assess their culture’s readiness for applying BSC.

Professor Kaplan’s keynote presentation was titled, “Leveraging data and Results to Drive Operations.” A highlight of his message was his describing how business intelligence (BI) and analytics (e.g., micro-segmentation, regression analysis for correlation, predictive analytics) are growing as key contributors to completing the last stages of the Kaplan and Norton Execution Premium Process (EPP) described in their most recent book. Those latter stages address optimizing decisions with analytics.

To summarize, these are the three shifts in BSC messaging I observed:
- Institutionalize BSC with software automation
- Create a culture for alignment of strategy to operations with metrics
- Apply business analytics to optimize

I suggest you revisit some of my prior blogs (and stay tuned for my future ones) to read how I agree with these emerging messages.

There seems to be a growing interest in applying analytics to sports. One example is the popularity of the 2003 book Moneyball that describes the depth of analytics that general managers like Billy Beane of the Oakland Athletics apply to selecting the best players, plus batter and pitcher tactics based on the conditions of the team scores, inning, number of outs, and runners on base. I expand on this trend in an article titled Baseball + Analytics = Improved Performance. Why might this interest be?

Perhaps it is because people are so stressed with their hectic workday and family responsibilities that taking interest in sports events is a great release of tension. (Of course there are the gamblers, but they are a subset.) Can we detect from this trend of sports analytics the application of analytics in business?

One of my co-workers at SAS, Retha Keyser, recently shared with me an astute observation on how managers mature in applying progressive managerial methods. She noted that roughly 50 years ago, CEOs hired accountants to do the financial analysis of a company, because this was too complex for them to fully grasp. Today, all CEOs and mainstream businesspeople know what price-earnings (PE) ratios and cash flow statements are and that they are essential to interpreting a business’ financial health. They would not survive or get the job without this knowledge.

Retha then recognized that 20 years ago, CEOs of companies did not have computers on their desks. They did not have the time or skill to operate these complex machines and applications, so they had their secretaries and other staff do this for them. Today you will become obsolete if you don’t at least personally possess multiple electronic devices such as laptops, mobile phones, BlackBerrys and PDAs to have the information you need at your fingertips.

There are hundreds of examples of applying analytics to sports. One I recall is the IT analyst Steve Miller’s solution to debunking a conjecture of his son’s friends that a certain university had low academic standards and thus fielded better athletes. Steve's article Yuletide Lite Plus a Few Graphs describes his solution.

You cannot manage what you cannot measure. Raw data leads to information. Information can then be analyzed for decision making. Competency with analytics will surely provide a competitive edge for organizations that these skills with workers at all levels.

On the shelves in the business topics section of any bookstore are numerous books about leadership and management. I have never considered myself a motivational writer or speaker that describes the importance of executives’ rallying the workforce with inspiration. In my career I have seen examples of leadership that reflect their individual desire for power more than a duty to improving organizational performance. My writing and speaking interests are more with equipping managers and employee teams to help their organizations be better, faster, cheaper, and smarter.


Muscle or brain. Strength or smarts. I choose the latter in both cases.


The primary source for improvements in organizational effectiveness and decision making is shifting toward the use of analytics of all flavors. Traditional approaches like 1980s management by objectives (MBOs), bullying employees, and hollow wall banners of rhetoric (“Quality Comes First”) are being superseded by deploying and integrating analytics.


Applying analytics from the CEO’s top desk to each employees’ desktop enables an organization to solve complex business problems, manage performance to achieve measurable objectives with targets, drive sustainable growth through innovation, and anticipate and manage change. Just having a foundation for analytics is important too, and Ann All describes this well in her blog Process Management Is Weak Link in Real-Time Data Chain. She observes, “ … companies are having and will continue to have problems with all of the data they are collecting. It takes time and effort to run reports and get them to the relevant people and additional time for those people to tell the relevant systems what to do, assuming the right systems are in place.”


In particular a powerful flavor of analytics is predictive analytics. Applying predictive analytics results in making proactive, forward-looking decisions that go beyond low end query-and-reporting questions like "What happened?”, "How many?" and "How often?" to answer high-impact questions like “Why did it happen?”, "What will happen next?" and "What is the best that can happen?"


I credit the New York Times op-ed columnist Maureen Dowd for my blog title. Her column was “Less Spocky, More Rocky” describing politicians; but when I applied this title to mission-directed organizations, like yours, I swapped the two names. I would prefer to have an organization with Star Trek’s Spock-like logic and analytical skills than one like Rocky Balboa punching meat carcasses in a freezer.

In Peter Evans-Greenwood’s recent blog, Inside vs. Outside, he builds a case that it is not sufficient to shift from an organization’s internal historical view of information to react to towards a predictive view of information. To clarify, he means that awareness of external forces, such as changes in market preferences, is critical. His accusation is that organizations may get excessively pre-occupied by over-analyzing their existing internal data, the traditional space of business intelligence (BI). He suggests this creates an imbalance that should be corrected by greater emphasis on future impacts and the opportunities that can come with them.

He uses the example that traditional applications of BI in the music industry of monitoring and analyzing its sales of CDs obscured seeing the ominous signals from the rise of iPod and iTunes and their adverse impact on CD sales. I really like the diagram in Peter’s blog titled “Time and distance drive the value of information.”

Peter’s article has made me re-think my blog Rearview Mirrors or Windshield? In that blog I made a case that that despite all the buzz about applying predictive analytics, for most organizations there continues to be an untapped treasure trove of historical information to analyze and learn from. Peter’s article does not make me consider that an organization should reduce its efforts on analyzing historical information. It makes me believe even more emphatically that organizations need to expand their efforts much more with applying backward and forward looking analytics and to be even more inclusive of external and exogenous forces for opportunism.

James Taylor, one of the IT analyst thought leaders of the broadening scope of business intelligence, has written a thoughtful piece titled Analytics simplify data to amplify its value. In his article James states that he likes his article’s title as a succinct description of analytics. He states:

(Simplifying data to amplify its value) always struck me as going to the core of analytics – the power of analytics to turn huge volumes of data into a much smaller amount of information and insight. … In every case the analytics are simplifying the data (a picture, a graph, an equation not thousands of rows of data) and yet amplifying its value by showing a data consumer what the data means. … IT people need to educate themselves on the role of these different kinds of analytics and their potential. … . Your systems store and manage data so something that makes that data more valuable makes your systems more valuable.

There is some danger when people talk about the keep-it-simple-stupid KISS rule. They forget its corollary LOVE rule – leave-out-virtually-everything. Too simple may be insufficient to draw correct conclusions. James understands this balance, and he has been an advocate of good decision making regardless of all the buzzwords the IT community may use. Many organizations are drowning in data but often starving for information. I’m with James. Performance management methodologies imbedded with analytics of all flavors unleashes the potential power for good decisions buried in data from transactional systems.