Business Analytics: Fad or Fundamental?

Business analyticsFad or fundamental?

2 Business analytics Fad or fundamental? 1

Table of contents

1 Fad or fundamental?

2 Encouraging factors

5 Thwarting factors

7 Preventing the fad mentality

8 A final word


Fad or fundamental?

Chia pets, beanie babies, pet rocks, pogs, vegamatics, and silly bands. What is the common denominator between all of these? They exploded into the market, flourished, and then saturated our consciousness before fading into memory.

Now that many businesses have implemented or are planning to implement complex business analytics (BA), it raises the question, “Is this a sustainable, value-driven movement or will analytics be headed the way of the Furby?”

The fundamentals behind analytics have been around for many years under various trends and names. The most recent incarnation — “Business Analytics” — is currently a hot buzz term used as frequently to sell magazines and products as to actually discuss the capabilities that analytics can bring to an enterprise. As analytics evolves, it is likely that the terminology describing it will continue to change. It should come as no surprise, then, that some

in the business community have articulated a “been-there, seen-that-already” reaction toward it, but is that the whole story? Beyond the hype, as, for example, Gartner categorizes trends with its “Hype Cycle,” what are we really talking about when we use the term Business Analytics? When the dust settles, will it be considered a fad or a lasting capability?

Those answers depend almost entirely on the discipline brought to the field and the end-to-end capabilities that BA can provide to drive and realize tangible business value. Analytics, as it stands today, has the potential to become one of the most seminal movements in the hunt for business excellence. However, if some confounding factors overshadow analytic progression and adoption, the risk of a look-back in years to come on what analytics has accomplished could be less than satisfying.

The following figure represents factors that will likely encourage analytics to become a lasting capability or a fad:

Factors encouraging a lasting capability

•The“AgeofEmpiricism”•Imperativefornewwaystosolvebusinesschallenges

•Fact-basedapproachtobusinessdecisions•Decliningtechnologicalbarriers

Factors encouraging a fad

•Organizationalinabilitytotranslateanalyticsintoabusinessbenefitandvalue

•Businessanalyticsasa“SoftwareStory”•Buzzwithoutprovenvalue

Figure 1: Encouraging and thwarting factors for Business Analytics


Encouraging factors

If BA is to become a mainstay, it will likely be because of changes in the way organizations monitor and tackle problems and how they adapt to the inevitable changes, not because of the amount of information available or the current analytics software products on the market. Physicist Richard Feynman once remarked, “For a successful technology, reality must take precedence over public relations, for Nature cannot be fooled.”

So what is the reality? BA in the right hands, and applied in the right way by an embracing organization, has shown to make businesses more profitable and successful. In fact, a recent MIT study indicates that an organization’s per-share value can be increased by as much as $20 for every one dollar spent on data-driven decision making.1 However, for BA to sustain the traction it has gained, the people who employ the technology must get past the business community and media hype and understand the nature of the capabilities that it can actually provide to an organization. Analytics, at its core, is a means of supplying decision makers with the relevant data needed to make more informed decisions. In today’s business world, an organization can be drowning in data and making sense of it in a short time is becoming an increasingly important aspect of daily operations.

The “Age of Empiricism”Over the past decade, analytics has made inroads into many aspects of an individual’s daily life. Our newspapers, blogs, health studies, and the like are filled with data and resulting analytic statements. Over the past few years, there have been broad sweeping changes in the way people perceive value in analytics. When businesses learn to properly apply this technology to the problems at hand, the results can be exceedingly beneficial. For example,

what were once considered mild annoyances — pop-up ads that often seemingly read our minds and match our interests — have now made way for services like Netflix, Amazon, and Pandora to gather information about our tastes and suggest movies, music, services, and products that we are apt to like. As consumers, as we move from accepting to expecting the use of analytics, we enter the “Age of Empiricism.” Here are a few other significant examples of analytics in critical daily services: •Politics — Real-time polling and reaction to

international political issues•Media — Custom services based on prior

consumer choices•Weather — Predicting severe and daily weather

patterns based on complex statistical models and the blending of historical patterns with chaos theory and ensemble models

•Traffic — Calculating commute trends and merchandise movement efficiencies

•Advertising — Targeted ads based on specific consumer preferences and history

•Sports — Statistics to break down and improve outcomes/performance based on traditional and nontraditional data and patterns

•CustomerService — Heightened service tailored to each consumer — dynamic/adaptive services and next best offers

People have come to depend on these things in order to make informed decisions throughout the day, and as empirically enlightened business enterprises catch on, they can also realize the benefits that come from using analytics to improve their products and services to gain a competitive advantage over the competition.

In a business context, business analytics is not really an instant solution. It’s a way of doing things.

“The most valuable commodity I know of is information.2”

1 Strength in Numbers: How Does Data-Driven Decision Making Affect Firm Performance? Erik Brynjolfsson, MIT and BER; Lorin Hitt, University of Pennsylvania; Heekyung Kim, MIT. p. 16.

2 Richard Burger, George Davies, (2005) “‘The most valuable commodity I know of is information’”, Journal of Financial Regulation and Compliance, Vol. 13 Iss: 4, pp.324–332.


So what does the ability to draw on a store of factual information mean for a business in the most basic sense? That it is learning.

Imperative for new ways to make business decisions — the fact-based approachMany business leaders would agree that their businesses make an enormous number of decisions based on gut instinct or inherently subjective criteria. However, with many documented advantages of doing so, today it is becoming increasingly critical for businesses to be able to use current information available to them and move, as much as possible, to more data-driven decision making. For BA to become a mainstay instead of a fad, organizations should clearly understand the principles beneath the hype and not expect more from the technology than it can deliver on its own.

Remember, the most powerful computer in the world is useless without the knowledge of how to properly take advantage of the capabilities it offers. The value in BA lies not in the technology but in the way it is applied in an end-to-end way, and the massive amount of information available at any given moment necessitates that an organization reevaluate how it makes important decisions.

An organization looking to realize the full value of BA should make it a priority to use it in an effective way — as a means of dissecting and compiling information to contribute to a full, fact-based decision. A business that expects perfect, automatically generated solutions is one that is likely to experience some disappointment as the human users of such solutions search for subtle flaws in results. Analytics is not a one-size-fits-all technology that provides the ideal solution to a problem, but rather is a toolset that helps put that problem in a clear light. Additionally, the Law of Large Numbers is an important core component of many analytic solutions, as results must be viewed with a statistical versus an absolute eye.

An “informed decision” means just that the decision maker had the most current, relevant information at his/her disposal when making the decision. BA, when supported by a fact-based decision-making process, allows an organization to more readily make these types of judgments.

Mistakes, problems, and inefficiencies detected through analytics can be corrected with the potential to save millions of dollars. However, BA must be understood in the context of it being an end-to-end process of asking questions and solving problems through fact-based methods. This empirical approach helps decision makers avoid common biases, such as:

•Sunkcostbias — “We’ve come this far so we can’t change course now…” — There is a natural tendency within organizations to look at the amount of time and money invested in their current practices and rule out alternative solutions, even if it is likely to become more profitable in the long term.

•Availabilitybias — “Watch out for sharks! Swimming in the ocean is dangerous!” — This speaks to the tendency for a large area of beaches to close due to a single shark sighting. Within a business, one statistical anomaly can have a far-reaching impact on a company’s short- and long-term policy if the circumstances around that anomaly are not fully understood.

•Confirmationbias — “That just proves my point.” — It is proven human psychology for an individual (or a business) to try to interpret new information to further demonstrate what they already believe to be true.

•Anchoringbias — “I think this weighs 150 lbs. What’s your guess?” — If a CEO says that they estimate a table to weigh 150 lbs, and then invites employees to guess, there is a tendency for those answers to be closer to 150 lbs rather than a much higher or lower number. The 150 lbs becomes the anchor around which the other guesses are based. In business, it is easy to see how common this phenomenon can become if relevant data and a different prompt/response structure is not there to provide context.

These are just a few of the many mistakes that can be corrected by properly utilizing BA to supplement current methods through an overall fact-based decision-making process. It will be up to individual businesses to contemplate these examples and decide how BA can help them avoid these behavioral, economic, and cognitive bias pitfalls in their own practices.


Declining barriers in technologyAnother encouraging factor in the movement for BA to become a sustainable tool is that technology is continuously getting cheaper, smaller, and more efficient. For a capability that is largely dependent on computing power and disk capacity, the declining costs of hardware and software have greatly reduced the technological barrier that stands between an organization with successful BA and one without.

The following figure represents the exponential growth in technology storage capacity:

Advances in modern technology make this aspect one of the more significant factors in pushing BA toward becoming a sustainable capability. Not many would argue that BA can be a beneficial tool; however, in the past, the costs associated with obtaining, developing, and implementing the necessary technology had many executives pondering whether the value gained would actually be worth the hassle and expense of switching out their current technology for more advanced analytics.

This focus on return on investment (ROI), and the costs that used to be associated with implementing a BA process, is what kept many organizations from taking a more active look at analytics in the first place. No more. Decreasing storage costs and increasing processing power reduce the required ROI to invest in BA infrastructure and related solutions. In business today, analytics has become the prime example of being able to do more with less.

Figure 2: Growth in storage capacity: A declining technology barrier

Source: Deloitte Development LLC 2012.

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With the many benefits suggested in the above dialogue, is there still a possibility that BA can become a fad? Absolutely. However, organizations should first ask, “Is there something inherent in the technology that will keep it from becoming a mainstay in the business world? Or are we simply not attacking the problem from the right angle?” While analytics can be a complicated solution to implement successfully, the problems arising from such efforts usually come from one of two root causes: The first stems from an organizational inability to translate analytics into business value; and the second can be broken down into two main aspects: the “Software Story” misconception, and the “Blah-Blah-Blah” of overexposure where there is much discussion but little confidence in demonstrable value.

Inability to translate analytics into business valueA business that is not profitable will not be in business for long. The number one reason behind most business practices is that they generate value to invested constituents, and the main reason analytics could become a fad is if businesses fail to realize the value that the technology can provide. BA can be a complicated process that depends as much on human interpretation as it does on core technologies and available internal, external, and synthetic data.

So what is going to make this a fad? The biggest thing is not generating value. An organization’s inability to execute a BA solution is probably the biggest risk. When an organization fails to create the proper decision-making atmosphere necessary to support the analytics technology, there is a tendency to blame the technology first. Who wants to admit that they could have done a better job with the technology and data they were given?

The important thing to remember is that while the basics behind analytics go back decades or even centuries, there is also a very human aspect to the whole endeavor. When an organization fails to realize certain goals it has set for its use of analytics, either through overestimation, human error, or organization change challenges, there is a natural tendency to believe that BA is not really as beneficial as envisioned. This can lead an executive, already skeptical from years of analytics hype and other less than fully successful big initiatives, to look at these shortcomings and say, “See, I told you so.” It is this type of misconception that can undoubtedly tip the BA scale to the “Fad” side.

This failure to realize business value in analytics, for whatever reason, is the main factor for organizations to potentially dismiss BA as a fad. Even businesses that do the analytics correctly but do not embrace the results or change their way of thinking can doom an otherwise beneficial endeavor to failure.

BA as a software storyAs a quick experiment and to demonstrate a point, type “Business Analytics” into an Internet search engine. Chances are that your search turned up more commercial softwares than actual discussions of BA as a capability. This is another leading cause for BA becoming a fad, and it ties back into the previous discussion of businesses failing to create the proper decision-making atmosphere to support the analytics technology.

Purchasing the appropriate hardware and software to fit an organization’s needs is an integral part of implementing a BA solution, but simply too many businesses stop at that point. BA software providers, in business to sell products, can provide tools that overemphasize ease-of-use and “do it yourself” features only to have customers find that the devil-in-the-details issues are more than they thought. A result can be that such software ends up becoming more “widgetized” than functional. The belief that the “widget” will get you there is mostly misnomer, and it can lead businesses to underinvest, undercommit, fail to realize potential value, and ultimately dismiss BA as a fad.

Thwarting factors

“Knowing a great deal is not the same as being smart; intelligence is not information alone but also judgment, the manner in which information is collected and used.”—CarlSagan


Think of analytics as a toolbox. One screwdriver of a particular size and style isn’t going to build you a chest of drawers — much less so in the hands of an inexperienced carpenter.

It should be understood that every business faces its own specific set of challenges. By expecting a software product to automatically solve these problems, organizations risk dooming analytics from inception — analytics should not be considered a piece of technology but rather a complex capability that businesses should build and a culture they should live with.

The “Blah Blah Blah” of overexposure“Business Analytics. Business Analytics. Business Analytics.” Some may believe that if said in the mirror five times, the ghost of analytics will appear and solve all of an organization’s problems, while the executives kick back and count stacks of money. Sadly, examples of this happen every day in business. The sheer volume of “software-story” products and (mis)information that exists has left a lot of executives either at a standstill, unsure of how to best approach the situation, or blindly charging into a complex process without being fully committed to the organizational changes that BA requires to generate value.

This media overdose on analytics has led to some troubling misconceptions:•Poor-qualityimitations — While success breeds

imitation, and imitation is the sincerest form of flattery, poor-quality imitators can have a significantly negative impact on an organization’s perception of the value analytics can generate.

•Oversimplification — Some software companies, trying to sell their products, can make BA out to be a simple push-button process, inevitably leading to customer mistrust when it fails to produce the expected results due to misuse, overuse, underuse, or the product’s intrinsic shortcomings.

•Cheapeningofeffortandvalue — After being led to believe that a BA solution can “deliver the world” by virtue of merely purchasing the software, a business may neglect to put in the necessary time and effort to truly integrate the analytics technology into an overall process.

•Overselling — “It slices, it dices. It’s everything you need!” Again, an example where software companies may provide potentially seldom-used features to sell product. Overexpectation may lead to frustration at the failure to produce expected results.

•Pavingthecowpath — The story goes that when deciding the new street layout for a city, planners decided to simply “pave the cow paths” instead of deciding on a new logical layout that would be more efficient for changing technologies. This failure to step back and think big picture in a new and fresh way is a common trap many organizations can suffer if they overly depend on the oversimplification or naïve interpretation of analytic possibilities.


The recent explosion of analytics into nearly all aspects of our lives has become both a boon and a burden. The benefits are there, yet doubts about sustainability remain. With so much potential value resting on the perceptions of those who will be or already are investing significant time, money, and energy into analytics, it becomes the burden of those who understand the process/technology to make reasonably certain that BA does not become a victim of market oversaturation. By following a few of these basic principles, individuals “in-the-know” can have an impact on whether analytics becomes a fad to be looked back on or a lasting value-driven capability:•Deliverinnovationwithexcellenceandakeeneyeonvalue— Companies should be willing to design BA products, solutions, and processes with focus on ROI rather than flash. As long as the focus on value remains an integral part of the equation, it can help rule out any misconceptions of “Is this really worth it?”

•Pushfortruecreativityandpushtheenvelope — For BA to help reach new frontiers of business performance, it may depend on the willingness of all of a company’s executives and their departments to truly push the boundaries of what is possible through analytics. Companies should think and go “outside the box” to approach increasingly complex problems.

•Changepeople’sapproachtobusinesschallenges — Change is consistently unsettling, even when it is for the better. For analytics to take hold, organizations should reevaluate the way they approach problems and how they adapt and change to solve them. Businesses should be willing to make changes in the way they operate if the analytics suggest better alternatives. BA has the potential to virtually eliminate many common malpractices within an enterprise. The caveat being that the organization must be willing to look at problems from new angles and understand that BA is not a “thing” but rather an end-to-end process that requires constant human involvement and feedback.

•Bearelentlessmissionaryandevangelist— As BA continues to evolve, organizations and individuals passionate to further the cause should constantly and consistently talk, educate, and innovate to show their company the appropriate way. BA is not a people replacer — but rather often a people retooler. Analytics leaders should work to excite and delight their companies with new, innovative, and high-value business solutions.

•Self-policetheindustry — At the end of the day, there is no analytics guardian angel that will determine that people are making the appropriate judgments about BA. It is up to individuals who understand the concepts behind the technology to educate and redirect the potentially misinformed. Correcting misguided assumptions or long-standing tradition is often no easy task. However, for organizations to fully realize the value that BA has demonstrated, this type of grassroots groundwork is necessary.

Preventing the fad mentality

With the massive amount of literature being generated in relation to BA, it is a critical time to step back and take a look at the whole picture and ask many questions. For example, what really is BA? What do businesses expect from analytics technology? What are the fundamentals behind an organization’s current decision-making process? What value can analytics produce for a company? Are a company’s people ready for change? And on and on, the questions go. By making sure that these questions are asked and sufficiently answered from the beginning of a BA implementation, organizations can take steps toward getting past the misconceptions and fully realize the capabilities of the technology. Only then, can they make a careful assessment of the value BA can provide.

The future of analytics lies in the hands of those using it. Whether it becomes a fad or a fundamental tool will depend on the discipline organizations can bring to the field and the degree of success with which they integrate BA into an overall culture of fact-based decision making. It is, at its core, a human story with an ending that has yet to be decided, but an ending that should be able to produce great value.

A final word

This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication.

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Copyright © 2012 Deloitte Development LLC. All rights reserved.Member of Deloitte Touche Tohmatsu Limited

JohnLuckerPrincipalGlobal Advanced Analytics & Modeling Market Offering LeaderDeloitte Consulting LLP+ 1 860 725 [email protected]

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