The Unnoticed Analyst: Can analytics succeed while going unnoticed?

The classic Harvard Business School case “Otisline (A)”1 begins with the quote, “… our objective is to go unnoticed.”

Bob Smith (not his real name), source of the quote and Chief Operating Officer at Otis Elevator, knows that elevators tend to remain well under the radar screen until they break. In the elevator business, you can be hugely successful and highly profitable by going unnoticed.

In the global economy, can analytic practitioners be hugely successful in their careers while going unnoticed?

Midway through an ethnographic analysis of the role of analytics in large, global enterprises, I find myself struck by the relative invisibility of analytics and analysts, the people who specialize in analytics.

Despite the laudable efforts of analytic evangelists such as Michael Lewis (Moneyball), Tom Davenport (Competing on Analytics), Jim Davis (The Information Revolution) and Ian Ayres (Super Crunchers), analysts, for the most part, remain hidden in the shadows while analytics remains a mystery to most C-level executives. Should we, as a community, be mobilizing to capture more mind share at the top of the enterprise?

Selling Analytics

It would be interesting to commission a study from one of the big research firms and ask a broad subset of the planet’s population what first pops to mind when they hear the word “analytics.”

Researchers at the IT Leadership Academy are doing just that in Global 2000 enterprises. The CIO’s response tends to be “reports” (61 percent of the population). Successful CMOs give an answer that includes a subset of “how I do my job/how we generate value/how we deliver on the promise of the brand.” And the people who actually do analytics give all kinds – and lengths – of responses.

However, no one is saying “before we can do analytics we must explain the take-to-the-bank value of analytics to decision makers.” In other words, analysts, the practitioners, have to sell analytics, the discipline.

Our Blind Spot

If one were to write the definitive history of analytics in the modern age, the RAND Corporation would receive significant ink. Like the Institute for Advanced Analytics at North Carolina State University, the Central Michigan University Research Corporation BI Forum and the SAS campus in Cary, North Carolina, RAND is a haven for high-intellect practitioners of quantitative problem solving.

Many sacred spaces of analytics have historically had a blind spot – understanding the behaviors of the humans who materially affect the creation of analytical outputs (primarily bosses and funding sources). Often in our profession we become so intent and so fascinated with quantitative problem solving that we lose sight of the human context in which those problems reside.

Franklin R. Collbohm, former test pilot, right-hand man to the head of Douglas Aircraft during World War II and founder of RAND, recognized this blind spot and asked for help:

“Well, we think we know a lot about planes, and other devices, but there’s one thing we don’t know much about, and that is a certain machine that weighs – oh, between 160 to 185 pounds, is between five-feet-eight and six feet, and is called a ‘pilot.’”2

Remember – RAND’s sole funding source was Air Force generals (i.e., pilots). If we are to optimize the value generated by analytics, we are going to have to humanize our in-organization behaviors. In today’s world, analytics is a product/service that must be sold.

Salespeople will tell you that the basis of sales success is having a great product (which we have) and a strong relationship beachhead from which to pitch the product.

George Washington knew that ultimate victory would not be accomplished on the battlefield, but in the hearts and minds of those engaged. In other words, public relations matters. Washington, despite losing more battles than he won, was eulogized as being “first in war, first in peace, first in the hearts of his countrymen.” When you are gone, will analytics be first in the hearts and minds of your CEO, your CMO and your board of directors?

True victory lies in capturing the imagination, respect and energy of a broad and diverse set of stakeholders, including suppliers, customers and executives.

As analysts, we need to expand the organization’s “smartwidth” – its capability to understand and act on information. Broadband gives us more information. Smartwidth gives your organization more understanding regarding what all this information means.

That’s what executives are looking for: meaning and insight from existing information sources. And that’s what analytics provides. It’s up to us to make that connection clear and start getting noticed as the smartwidth source. Our objective, after all, is NOT to go unnoticed.

This article was republished with the permission of sascom Magazine.

Sources

  1. F.W. McFarlan and D.B. Stoddard (July 15, 1990). Harvard Business School 1995-96 Catalog of Best-Selling Teaching Material; Ref No. 9-186-304. The case instructs students in the value of deconstructing an industry into its component parts. (The elevator industry can be divided into two buckets – new equipment sales and service.) The case illustrates how information technology, innovatively, insightfully and courageously deployed, can change the structure of an industry.
  2. Alex Abella, Soldiers of Reason: The RAND Corporation and the Rise of the American Empire (NY: Harcourt Inc., 2008).

About the Author

Thornton May, Executive Director and Dean at the IT Leadership Academy, is one of the premier visionaries in the IT industry. His book, The New Know: Innovation Powered by Analytics (Wiley and SAS Business Series), positions analysts as heroes of the age we are about to enter.

Run New and Old Performance Measures in Parallel

The outcomes of substantive change can seldom be fully anticipated; and changes to organizational performance measures are no exception. Performance measures drive executive and managerial decisions and personnel actions and, over time, shape these behaviors to achieve optimal results relative to the established measures. Thus, changes to performance measures serve to change behaviors in predictable and sometimes unpredictable ways.


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Eight Levels of Analytics

Not all analytics are created equal. Like most software solutions, you’ll find a range of capabilities with analytics, from the simplest to the most advanced. In the spectrum shown here, your competitive advantage increases with the degree of intelligence.

1. STANDARD REPORTS
Answer the questions: What happened? When did it happen?
Example: Monthly or quarterly financial reports.
We all know about these. They’re generated on a regular basis and describe just “what happened” in a particular area. They’re useful to some extent, but not for making long-term decisions.


2. AD HOC REPORTS
Answer the questions: How many? How often? Where?
Example: Custom reports that describe the number of hospital patients for every diagnosis code for each day of the week.
At their best, ad hoc reports let you ask the questions and request a couple of custom reports to find the answers.


3. QUERY DRILLDOWN (OR OLAP)
Answers the questions: Where exactly is the problem? How do I find the answers?
Example: Sort and explore data about different types of cell phone users and their calling behaviors.
Query drilldown allows for a little bit of discovery. OLAP lets you manipulate the data yourself to find out how many, what color and where.


4. ALERTS
Answer the questions: When should I react? What actions are needed now?
Example: Sales executives receive alerts when sales targets are falling behind.
With alerts, you can learn when you have a problem and be notified when something similar happens again in the future. Alerts can appear via e-mail, RSS feeds or as red dials on a scorecard or dashboard.


5. STATISTICAL ANALYSIS
Answers the questions: Why is this happening? What opportunities am I missing?
Example: Banks can discover why an increasing number of customers are refinancing their homes.
Here we can begin to run some complex analytics, like frequency models and regression analysis. We can begin to look at why things are happening using the stored data and then begin to answer questions based on the data.


6. FORECASTING
Answers the questions: What if these trends continue? How much is needed? When will it be needed?
Example: Retailers can predict how demand for individual products will vary from store to store.
Forecasting is one of the hottest markets – and hottest analytical applications – right now. It applies everywhere. In particular, forecasting demand helps supply just enough inventory, so you don’t run out or have too much.


7. PREDICTIVE MODELING
Answers the questions: What will happen next? How will it affect my business?
Example: Hotels and casinos can predict which VIP customers will be more interested in particular vacation packages.
If you have 10 million customers and want to do a marketing campaign, who’s most likely to respond? How do you segment that group? And how do you determine who’s most likely to leave your organization? Predictive modeling provides the answers.


8. OPTIMIZATION
Answers the question: How do we do things better? What is the best decision for a complex problem?
Example: Given business priorities, resource constraints and available technology, determine the best way to optimize your IT platform to satisfy the needs of every user.
Optimization supports innovation. It takes your resources and needs into consideration and helps you find the best possible way to accomplish your goals.


The best analytics for your business problem
The majority of analytic offerings available today fall into one of the first four areas, which report historical data on what happened in the past but no insight about the future. For simple business problems, these analytic solutions will be all you need. But if you’re asking more complex questions or looking for predictive insight, you need to look at the second half of the spectrum. Even better, if you can learn to use these technologies together and identify what type of analytics to use for every individual situation, you’ll really be increasing your chances for true business intelligence.

This article was republished with the permission of sascom Magazine.


About SAS – Providing organizations with THE POWER TO KNOW® since 1976.

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About sascom Magazine

sascom Magazine is the quarterly publication of the SAS Institute, Inc. Each issue is packed with thought-provoking content and insight into the business issues that affect all companies competing in today’s technology-driven marketplace with recent contributions by best-selling author and researcher Tom Davenport; social media guru Chris Brogan; and Myron Scholes, world renowned economist and Nobel Prize winner. Subscribe now to get your subscription to this award-winning quarterly magazine. sascom Magazine can also be accessed online at www.sas.com/sascom.

Identify the Measures First

“Not everything that can be counted counts, and not everything that counts can be counted.”

Albert Einstein
Awarded the 1921 Nobel Prize in Physics, named Time’s Man of the Century in 1999, and best known for his conception of the theories of special and general relativity

Organizations today seem to have a never ending supply of performance measures. Our data rich environment feeds the need of many managers to have all things counted. Yet as Albert Einstein suggests, not everything that can be counted matters. And just because something is counted doesn’t make it important. Thus, not everything that is measurable should be assigned its own performance indicator; rather only those things that are truly important, whether currently counted or not, should be measured. The identification of performance measures should therefore start with the identification of the key factors critical to the organization’s success.


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Additional Information

The following StrategyDriven articles and whitepapers provide additional information on the identification of those performance measures important to the organization’s ongoing success:

Articles

StrategyDriven Podcast – Special Edition

Whitepaper

Resource – Book

Multiple Action Thresholds

Recovery from a significant event is costly and disruptive. While an expense, mitigating and preventing activities taken to prevent the event’s occurrence are typically far less expensive. From a business perspective, the challenge becomes that of balancing the value of risk reduction with that of the mitigating and preventative activities’ cost.


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Additional Information

Additional information regarding organizational performance measures and their thresholds can be found in the StrategyDriven whitepaper series Organizational Performance Measures.