Analytics and EPM – You’ve read me, now hear me

I wrote my first weekly SAS blog in February 2007, almost 5 ½ years ago and have rarely missed a week. So you have read me. In this blog I deviate from the normal for you to hear me. I discuss business analytics and enterprise performance management (EPM).


INFORMS podcast

This link is to a 30 minute podcast where I discuss analytics. It was recorded by the Institute of Operations Research and the Management Sciences (INFORMS). Click on this link:

 Gary Cokins’ INFORMS podcast May 25, 2012

In the podcast I describe what I wrote in these two published INFORMS articles.

-   The Obstacle Course for Getting Buy-in for Analytics

 -  Do Companies Fail Because of Irrational Decisions?


Computer Aid Inc. IT Metrics & Productivity Institute

There is a small fee to listen to my talk but downloading my slides is free from ITMPI. You will need to first register. My talk is titled:

Implementing Enterprise Performance Management (EPM) Methodologies?  – Pitfalls and Speed-Bumps  



I enjoy writing but talking is fun too!

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Being wrong versus being confused

Which is worse? Being wrong or being confused?

Let’s start with some definitions.  To make a wrong decision means you were mistaken and erroneous. Your decision was incorrect for the problem to be solved or opportunity that could have been realized. (There is also an immoral, unethical, and illegal connotation; but that is a different variation of a poor choice. To be confused means you are baffled, bewildered, and perplexed. You cannot be positioned to make a correct decision because your thinking is muddled and clouded.

Embracing analytics can resolve both conditions.

Cultural issues related to wrong choices

An example of being wrong might be if you purchased a large top load clothes washing machine that did not fit in the space that a traditional front loading washer would have fit. Using the same example, being confused would be if you did not understand the differences between the two types of washers in terms of benefits, water consumption rates, and so on. The result typically is you postpone the decision.

Postponing a decision from being confused reduces the risk and possibly the embarrassment of making a mistake but it also can mean missing the opportunity to have gained. Both involve risks. Different cultures approach risk in different ways.

Geert Hofstede, a Dutch researcher in social psychology, has authored provocative research about Eastern versus Western culture’s attitudes toward risk that sheds light on multi-cultural differences with risk appetite and decision making. One of Hofstede’s studies developed an Uncertainty Avoidance Index (UAI) that measures a nation’s (or a society’s or organization’s) tolerance for uncertainty and ambiguity – its appetite for risk.

To abbreviate the details of the study’s findings, it is convenient to describe the two countries with cultures representing opposite and extreme ends of the UAI continuum. By better understanding these contrasting behavioral differences, project champions striving to successfully business analytics may better succeed. In Hofstede’s study, UAI scores can range from 0 (pure risk takers – such as casino gamblers) to 100 (pure risk avoiders – very cautious and conservative). Of all the nations, Americans ranked lowest implying fewer rules, less attempts to control outcomes, and greater tolerance for a variety of ideas, thoughts, and beliefs. In contrast, Japan ranked highest in its UAI score implying high levels of control in order to eliminate or avoid the unexpected. A type of culture such as Japan does not readily accept change and is risk averse.

Is your decision making an Eastern or Western type?

How can UAI apply to managing organizations? My belief is there are obstacles and barriers that are slowing the adoption rate of business analytics. They are no longer technical ones but rather involve people, culture, and human nature’s resistance to change.

How would you personally assess the UAI of the organization you are employed by or one you keep an eye on or am involved with? Does it have a low UAI (USA-like)? This implies having self-concerned employees, less conformity, reliance on intuition and gut-feel to “wing-it”, avoiding rigid rules, low acceptance of authority, low trust levels, and reasonable tolerance for conflict, tension, and dissent.

In contrast, is your organization at the other extreme with a high UAI (Japan-like)? This implies being collectivist with needs for consensus, more conformity, very analytical, strict and enforced rules, high acceptance of authority, high levels of trust, and little tolerance for conflict.

Implications for success with analytics

Ultimately all organizations will need to create a culture for analytics and fact-based decision making. Regardless of an organization’s type of culture, what this all means is we must elevate the importance of organizational change management and behavior modification.  Inevitably we will need to learn change management as “on the job” training.

So which is worse? Being wrong or being confused. They are both bad with adverse consequences. Why not be smarter and safer at the same time?

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Analytics for creating more choices

Choice covers both the capacity to control people and events, and an underlying belief in the possibility of such control. Being able to rule your environment gives power to self-determination, even for babies. In a study, researchers attached strings to the arms of infants “as young as four months.” When they moved their arms, music played. The babies grew “sad and angry” when researchers removed the strings and they could no longer make music play, though music continued sporadically.

Wanting to choose comes naturally, though it isn’t linked to any distinct biological advantage. Without choice, as zoo animals show, even if someone else’s decisions set you up in luxury, you won’t be happy. Having influence on control makes people happiest. A nursing home let some patients decide when to watch movies and which plants they wanted. After six months, those who had more perceived choice “were happier and more alert” and, it turned out, “were less likely to have died.”

People define themselves through their choices

The studies just described come from the book The Art of Choices written by Sheena Iyengar, a professor at Columbia University. In her book, Iyengar makes these observations. The way that people make choices as individual consumers of products and services has changed with industrialization. Buying was once very matter-of-fact due to limited options, but it has been transformed into collecting markers of personal identity. As “an ethos of independence” took over, getting noticed as an individual replaced blending in, and choice became an exercise of personal definition. Think Starbucks, automobiles, or clothing fashion. Now, people everywhere face substantial new alternatives. Options for family structure, political affiliation, and even eye color (with “tinted contact lenses”) let people express themselves in countless ways.

Iyengar continues by stating that along with freedom, these decisions carry the burden of defining a person’s self-image. She describes three challenges make this hard: People believe they are more unique than they are, they want a consistent vision of themselves, and they want it to mesh with others’ views of them. With each potentially immobilizing choice, people define themselves privately and socially. Iyengar’s solution: Try to see your identity as ever changing, so that choosing helps you discover yourself.

If we replace organizations with people there are similarities.

The role of analytics to make choices for organizations

Analytics’ goal should be to gain insights and solve problems, to make better and quicker decisions with more accurate and fact-based data, and to take actions. “Big data” with high performance computing is allowing organizations to deploy business analytics to have more choices and make better decisions. But the three challenges that Iyengar describes also apply to organizations. For commercial companies they seek a competitive edge typically through differentiated products and services increasingly targeting differentiated customers.

Since customer preferences are not static – they are making individual choices on what to purchase – business analytics are essential to detect what is changing. They are also needed for organizations to uniquely define themselves. Ultimately the best source to gain a competitive edge is to grow competencies in employees with analytics – creating a culture for analytics.

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Tried and died. One and done. Learning from failures.

One of the frustrations I experience is when managers or analysts share with me that their organizations tried to implement progressive management methods, and they either failed or abandoned them. A prominent example is an unsuccessful attempt to implement activity-based costing to measure and manage costs and profit levels of products, services, channels and customers. Other enterprise performance management examples include risk management, customer analytics, enterprise resource planning (ERP) systems and the balanced scorecard.

What causes these failures or the quick loss of interest?


Experiencing failure is a foundation for success

What we are discussing here is a topic few wish to discuss – failure. I advocate having a positive view of failure and leveraging disappointing or botched implementations of an advanced managerial method or system as a learning experience. Failure can be a great teacher. Perseverance and determination is important for success. Don’t believe that one needs to avoid failure. You have to accept risk when taking on improvement projects. 

There are some inspirational lessons about early career failures by individuals who ultimately succeeded. Consider these:

  • Winston Churchill failed sixth grade, and he was subsequently defeated in every election for public office until he became prime minister at the age of 62.
  • Charles Schultz, the creator of Peanuts, had every cartoon he submitted rejected by his high school yearbook staff.
  • Twenty-seven publishers rejected Dr. Seuss's first book, To Think That I Saw It on Mulberry Street.
  • After film star Fred Astaire's first screen test, the memo from the testing director of MGM, dated 1933, read, "Can't act. Can't sing. Slightly bald. Can dance a little."
  • Henry Ford went broke five times before he succeeded.
  • Thomas Edison's teachers said he was "too stupid to learn anything," and he was fired from his first two jobs for being "non-productive."
  • Albert Einstein’s PhD thesis was rejected as being “irrelevant and fanciful.”


Is this not enough evidence that failure is just another name for experience?

To read further the rest of this article, please click on this hypertext from my monthly article I write for on May 3, 2012  titled “Tried and Died, One and Done: What to do with Failure.” The article concludes with this:


Lessons learned: Valid methods don’t die but go dormant

The ultimate lesson is that implementers should not underestimate the importance of behavioral change management and overcoming people’s natural resistance to change. This includes employees who are afraid of knowing the truth and do not want to be held accountable or measured.

My advice is to consider how much emphasis to place on three factors that, when combined, overcome resistance to change: discomfort with the current situation; a vision of what a better state looks like; and first practical steps (e.g., a pilot project or a rapid prototyping exercise). Many project champions dwell on the second one, a vision, by explaining the benefits of their proposed project. The key is to focus on the first factor by creating discomfort in managers and co-workers. Constantly ask, “How long do we want to continue to make decisions with flawed, misleading or incomplete information?” That creates the interest in the vision – a solution. 

After a tried-and-died project fails, the need that triggered interest typically does not go away. Like a hibernating bear, the project simply goes dormant. Inevitably managers will repeat the same questions, like “Where do we make or lose money?” There will always be a second chance to successfully implement the project. Learn from your failures. Do not underestimate the value of experience. Never lose hope.

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An analytics story problem: When will two trains collide?

I recently presented a keynote presentation at the annual conference of the joint Ohio chapters of the Institute of Management Accountants. I shared the stage with Mike Willis, Partner, PricewaterhouseCoopers and the founder of and Chairman Emeritus of XBRL International. Mike posed this question to make an important point:  

Two trains are on the same track 600 miles apart traveling towards each other.  One train is traveling west at 50 mph and the other train is traveling east at 20 mph.  How long will it take for the trains to impact each other? 

  1. 8 hours, 30 minutes
  2. 8 hours, 34 minutes
  3. 8 hours, 42 minutes

The narrow correct answer is #2. But an experienced analyst thinking out-of-the-box would ask (1) Who would ride on a train traveling 20 mph?  and (2) Who would put two trains on a collision course?

Framing a problem

In my mind there are two pre-requisites to problem solving: (1) first frame the problem or opportunity, and (2) then perform the analysis.

Framing a problem is usually not an easy task. Yes for simple plans, it is. For example, one decides to take an umbrella if the sky has dark clouds but not if it is sunny. Is one 100% sure? It is probably good enough for the umbrella decision. But do you know or just think you know?

This example gives a glimpse of the limits of planning. Mental shortcuts, gut feel, intuition and so on typically work except when problems get complex. When problems or opportunities get complex, then a new set of issues arise. Systematic thinking is required. What often trips people is they do not start by framing a problem before they begin collecting information that will lead to their conclusions. There is often a bias or preconception. One seeks data that will validate one’s bias. The adverse effect is we prepare ourselves for X and Y happens. By framing a problem, one widens the options to formulate hypothesis.

 Analytics begin with a hypothesis

Ah, the term hypothesis. Posing a hypothesis critical and requires analytics, the second pre-requisite, to prove or disprove if the hypothesis is valid or not. Much is now being written about analytics. There is a reason. The margin for error keeps getting slimmer. Also, once accepted types of strategies (e.g., low-cost producer) are vulnerable to competitor actions. The only truly sustainable strategy is to have organizational competency with analytics.

Experienced analysts frame, analyze, and then plan for actions. But plan to re-plan – numerous times. And today with high performance computing (HPC) there are ways to do this. Reliable forecasting and probabilistic scenario planning can be added to the portfolio of analytics that progressive companies use.

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Please put the shower curtain inside the bathtub!

I take risks as a blogger to use blog titles, like this one, that does not indicate the blog’s topic. So many readers will likely not read them. In addition, some of my blog do not contain “keywords” like business analytics for website search engines to detect and drive more traffic. That further reduces the circulation of my blogs. However, I know I have a substantial readership following on this and other websites from my page-count statistics, so this blog is for you.

What are key success ‘messages’ for business analytics?

My blog title is a quote from the famous hotelier, Conrad Hilton (1887-1979), who was the founder of the premier Hilton hotel chain (and great-grandfather of Paris Hilton). On the USA’s television program The Tonight Show with host Johnny Carson (who hosted 1962-1992 prior to Jay Leno’s era), Carson interviewed an aged Hilton as a guest. Carson asked him to reflect on his long career and successes and answer what “message” he had for the public. With great gravity, Hilton paused momentarily before turning to the camera. “Please,” he pleaded, “put the shower curtain inside the tub!”

Of course, the surprise is you were expecting a profound answer reflecting wisdom and experience. What Hilton answered was so basic yet revealing of his consideration of the extra work load of his hotel employees when the shower curtain is outside, not inside, the bath tub.

What is my message regarding analytics-based enterprise performance management?

In November, 2008 I did ask myself an indirectly related “what message?” question in my SAS blog titled, “What do I want my Epitaph and Legacy to Be?” I wrote after my death:

“I fear that someone will write my epitaph as: ‘Here lies Gary Cokins, who died a failure because his quixotic quest to convince organizations to adopt and integrate performance management methodologies (with imbedded analytics) fell on deaf ears.’ … I do have a good reputation for explaining enterprise performance management’s portfolio of integrated methodologies and solutions in ways that people can understand them. But that is not want I want to be remembered for. My desire is that I raised awareness that the impediments and barriers slowing the rate of adoption and integration of enterprise performance management methodologies are not technical – the software solutions are proven. The impediments are all social, such as human nature resistance to change, fear of knowing the truth, lack of executive leadership, lack of training, and so on. The key to success for implementing performance management is organizational change management and behavior modification. This is what I want to be remembered for.”

So, on a comparable level of Hilton’s simple but fundamental answer to the “what message?” question, mine would be: “When making enterprise performance improvements, do not underestimate how much people matter!”

Why do people matter so much to drive analytics?

If you have read my blog this far, then I imagine that you too have a passionate interest in organizations, possibly yours, to you use more fact-based information and analytics and less intuition, gut feel, and self-serving politics. Like Conrad Hilton’s message which ultimately if followed reduces the workload of a hotel house cleaning maid, I too often have a populist message like Will Rogers and Mark Twain. (As proof, read my “We’re Down Here” article.)

To advance the uses of analytics, think much more about how to overcome the social and cultural obstacles, not the technical ones. Technology is no longer the impediment. The obstacle is behavioral – overcoming resistance to change, fear of knowing the truth, and workers not wanting to be held accountable. You have to be psychologist to drive organizational transformation.

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Kaplan and Norton’s future vision of the Balanced Scorecard

I define Enterprise Performance Management (EPM) much broader than its narrowly perceived view as a CFO initiative with a bunch of dashboards. Under EPM’s broad umbrella are these component methodologies: (1) profitability analysis; (2) forecasting, planning, and budgeting; (3) customer intelligence; (4) process improvement; and (5) strategy execution. The last one, strategy execution, relies on strategy maps, strategic scorecards (with KPIs), and operational dashboards (with PIs).

 The creators of the strategy map and balanced scorecard concept, Professors Robert S. Kaplan and David P. Norton, recently wrote an article, “The future of the Balanced Scorecard.” I have excerpted below their five futures expansions. The two that caught my attention are the integration with enterprise risk management (ERM) and with business analytics. Software technology supports both, and my belief is software unifies EPM with all of these components. Here are the excerpts:

 Strategic Supply Chain Alliances and with Partners Too

Collaborate with external constituents, such as key suppliers, customers and alliance partners, to develop a strategy map that describes and communicates the strategic relationship. Once developed, the map and scorecard are used to govern and guide the relationship. Building these together creates trust and understanding across organizational boundaries and mitigates the cultural conflicts that are the prime source of failures in strategic relationships.

 Public Sector Government

Realize that cities and provinces, and even nations, around the world are using our framework for describing and communicating strategies for competitive advantage, and then successfully implementing their visions with our strategy execution system. As citizens around the world demand more transparency, accountability and performance from their governments, the benefits of using the BSC to focus and align public-sector entities will become even more compelling in the years ahead.

Empowering Risk Management

Use the strategy map as a jumping-off point for risk management, especially the identification and management of strategic risks. Much of risk management today is narrowly oriented around compliance and controls. While managing these risks is important, companies often neglect the inherent and unavoidable risks that arise from their strategies. For each strategic objective on their map, company managers should identify the risk events that could lead to failure to achieve the targeted performance. They can then quantify the likelihood and consequence from each identified risk event and develop key risk indicators and risk mitigation initiatives that serve to reduce the likelihood and/or consequences of the most significant risk events.

 Empowering Change Management

Use the strategy map as a central change management tool. Among the most important change management principles are building consensus among the guiding coalition and communicating the new vision and strategy clearly to all employees. Having the executive leadership team build the strategy map and scorecard together creates consensus and commitment among the team. The map itself has proven to be a great communication tool to reach the hearts and minds of all employees. The quantification of performance for strategic measures gives employees a deeper understanding of what they are being asked to accomplish with the new vision and strategy, and empowers them to act in a way that helps the organization succeed with its new strategy.

 Leveraging Analytics with BSC

Expand the role for analytics in the strategy execution system. One of our disappointments over the past 15 years has been the slow uptake by companies to allow more testing of their strategies. They can use BSC data to distinguish when disappointing performance is caused by poor execution of a good strategy, as opposed to when it has been caused by very good execution of a poor strategy. Data analytics can also be used to design operational dashboards by identifying indicators and metrics that best predict excellent customer and process performance. Additional analytic opportunities are integrated with a company’s activity-based costing system to develop customer profitability (and loss) metrics to include on the scorecard’s customer perspective.


 Are you motivated? Start small, but think big.

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Analytics takes the thumb off the scale

When I read an article written by Eric Garland, a strategic analyst, I was disheartened. Garland recently quit his job of 15 years as an analyst, and he expressed his frustration with decision makers in an article published in the Atlantic titled, “How So-Called Strategic Intelligence Actually Makes Us Dumber.” What is your reaction to this excerpt from his article?

“I am not quitting this industry for lack of passion, as I still believe – more than ever – in using good information and sophisticated analytical techniques to decode the future and make decisions. The problem is, the market for intelligence is now largely about providing information that makes decision makers feel better, rather than bringing true insights about risk and opportunity. Our future is now being planned by people who seem to put their emotional comfort ahead of making decisions based on real – and often uncomfortable – information. Perhaps one day, the discipline of real intelligence will return triumphantly to the world's executive suites. Until then, high-priced providers of "strategic intelligence" are only making it harder for their clients – for all of us – to adapt by shielding them from painful truths.”

My reaction was he has a point. Relying on intuition, self-interest, and office politics runs the risk of confirmation bias – believing in an answer before viewing the facts.


A preconception with bias

Weak leaders are prone to a preconception bias. They can be blind to evidence and somehow believe their intuition, instincts, and gut-feel are acceptable masquerades for having fact-based information.

Psychologists refer to this as a confirmation bias. What often trips managers up is they do not start by framing a problem before beginning to collect information that will lead to their conclusions. They often subconsciously start with a preconception. That is, they seek data that will validate their bias. The adverse effect is they prepare themselves for X and Y is actually happening! By framing a problem and considering alternative points of view, one widens the options to formulate hypothesis. And this is where the emerging discipline of analytics fits in. With fact-based information, organizations gain insights and views that they might otherwise have missed.

Mental shortcuts, gut feel, intuition and so on typically work except when problems get complex. When problems or opportunities get complex, then a new set of issues arise. Systematic thinking and application of analytics are required.

In the book Analytics at Work: Smarter Decisions, Better Actions co-author Jeanne G. Harris of Accenture notes that forty percent of important decisions are not based on facts but rather on intuition, experience, and anecdotal evidence. An immediate impression is this so sad. However, one ideology can take the position that perhaps intuition and experience is reliable for decisions – if the decision-maker has exceptional intuition and experience. But that is a pre-requisite. What if it doesn’t sufficiently exist? Just look at the 2008 global economic meltdown. There were many smart minds managing the global economy. And look at what happened.


Analysts’ imagination sparks creativity

In contrast, a curious person, which is a trait of analysts, always asks questions. They query data to answer questions, and then use analytics to ask further and more robust questions. And better yet, their analytics can answer their questions.

Analysts typically love what they do. If they are good with analytics, they infect others with enthusiasm. Their curiosity leads to imagination. Imagination considers alternative possibilities and solutions. Imagination in turn sparks creativity.

When analytics are applied, they take “the thumb off the scale” that managers use to influence the result of something that is in their favor. Eric Garland was a victim of too many heavy thumbs. As analytics is increasing embraced, fingers on the scale can be removed.

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Business analytics is a big sham and over-rated!

UPDATE: For anyone who comes across this post later in the year and might have cause for concern, please be sure to read the last paragraph, which includes the punch line for an annual April Fool’s joke that I play on my readers.


Analysts probing rationally integrated limits for optimization opportunities lack smarts. That is, most analysts who think they are successfully solving problems are foolishly kidding themselves and are delusional.

Let’s be honest. This new fad about business analytics is getting wildly over-blown as if it is comparable to a miraculous drug that stops aging or is a proof of physics’ Grand Unified Theory that Albert Einstein went to his grave failing to produce. Today’s business analytics is like the snake oil that was pedaled by hucksters in the 1920s. Using analytics gives false hope that it can improve an organization, solve problems, or exploit opportunities. It is dubious that analytics improve or solve anything.

And who are the hucksters spreading this sham? Of course, it is the consultants and software vendors. Don’t be conned by them.

All this interest in statistics, operations research, analytics, and optimization is someone’s pipe dream. It is this decade’s quackery. The interest in analytics will pass and fade away like any fad. Remember the pet rock? The advocates and followers of analytics are like a zealous cult. Be wary of them and their fraudulent ideas. Don’t believe their calculations – especially their so-called “predictive analytics.” You’d do better knowing the future with a crystal ball or ouija board.

Business intelligence – the big joke

And what is the big deal with business intelligence, the so-called BI? Anyone who uses the words “business” and “intelligence” in the same sentence is naïve and foolish. Operating a business does not require being intelligent. Managing a business is all about power. The best business managers hound their employees to squeeze results from them, and they crush their competitors with force.

Business intelligence has little to do with successful decision making.

Analysts waste every ones’ time

An additional exaggeration is the importance of analysts in an organization. Analysts are simply aimless number crunchers who perpetually spin their wheels with nothing to really show for their wasted efforts. The best decisions come from leaders who have a gift and a sixth sense to just know the right things to do. The best culture for any successful organization is to operate in a “no facts” zone.

Tom Davenport and Jeanne Harris wrote a book title Competing on Analytics. It is drivel. Don’t waste your time reading it. Companies compete by having more money. Those with more money win, and those with less lose.

And if you believe what I have written here, read the first letter of each word in the first sentence of this blog. You will see that together they spell A-p-r-i-l f-o-o-l-s!

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The waiter eventually arrives with the check

How long can an organization survive if it keeps making mistakes? How competitive can a company be if its decisions are bad ones? Who wants to have their organization continue to perpetuate making decisions with flawed, misleading, or incomplete information?


Organizations in a “no fact” zone

I continue to be intrigued that almost half of the 25 companies that passed the rigorous tests to be listed in the once famous book by Tom Peters and Robert Waterman, In Search of Excellence, today either no longer exist, are in bankruptcy, or have performed poorly. What happened in the 25 years since the book was published? Ponder this question, “How many of the original Standard and Poors (S&P) 500 list originally created in 1957 are on that list today?” Research from Professor Gary Biddle of the University of Hong Kong reported the answer is 74, just 15%. And of those 74, only 12 have outperformed the S&P index average. Pretty grim. A few years from now will the currently popular book, Good to Great by Jim Collins, reveal the praised companies as laggards?

Perhaps the explanation is that when an organization is does not have superior and timely information, it can be in jeopardy but not realize it. Each new day going forward requires making strategic adjustments to anticipate continuously changing customer needs and counter tactics by competitors. Analytics is about gaining investigating, gaining insights, and making good decisions.

My message here is for an organization to improve its competency with analytics, it must pay a price. There is no free lunch to enjoy gaining those insights through better and deeper analysis. The waiter does always eventually arrive with the check!


Analytics: a culinary delight

At the risk of overusing this restaurant analogy, paying the check will be more than worth it when the food is delicious and fulfilling – especially when one is hungry. However, who has lots of data but is starving for information? (Hands up all of you with transactional CRM and ERP systems – and allegedly business intelligence systems.)

Unfortunately, what can spoil a potentially good dining experience are unskilled cooks in the kitchen using low-grade or stale ingredients. A poor tasting meal adversely affects and reduces the amount of a waiter’s or waitress’ tip regardless how good their service is. Therefore the cooks (IT) and the waiters and waitresses (analysts) need to work together as a team. Unfortunately, a healthy relationship between IT and analysts is not always the case.


The wall between IT and analysts

There is a tall brick wall between IT specialists and analysts. There will need to be a shift from face-to-face adversarial confrontation to a side-by-side collaborative relationship to remove this wall. Part of the problem is how IT and analysts view each other.

Analysts view IT as an obstructionist and uncooperative gatekeeper of data without the skills to convert that data into useful information. Experienced analysts want easy and flexible access to the data and the ability to manipulate it. They want a set of capabilities for investigation and discovery. IT typically tries to prevent this. Analysts view IT as bureaucrats who manage a set of technologies and whose main goal is to keep the lights on.

In contrast, IT increasingly views users as competitors who may solve problems but don’t have to operate the solutions – they just make it harder to better manage capacity costs by using too many IT resources. And IT sees users as a risky group that has low regard for data governance and security.


The five-star restaurant experience

Ultimately both IT and its users will need to collaborate and compromise by better understanding and appreciating each other’s changing roles and needs.

Imagine that your organization has overcome the barriers and obstacles to fully embrace analytics. Let’s then dine at “(fill in your organization’s name) Bistro.” They know how to cook great cusine – to convert ingredients (data) into cuisine (information). If this restaurant is truly your organization, then I enthusiastically say to the customers (the business users), “Bon Apetit!”

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