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Business Intelligence and a Culture of Analysis

Originally published January 13, 2009

For business intelligence to thrive in an enterprise, that enterprise must have a culture of analysis. Business intelligence, as we have often reminded ourselves in these articles, is another name for analytics; and this function is carried out by analysts, knowledge workers or individuals in other similar job descriptions. These are basically people that work with data and information and do…analysis.

The OnLine Dictionary tells us that analysis – at least the most relevant definition for our purposes – is “the separating of any material or abstract entity into its constituent elements.” Even more interesting is to look at the definition from thesaurus.com: Analysis is examination and determination. And its list of noun synonyms includes: breakdown, dissection, dissolution, division, inquiry, investigation, partition, reasoning, resolution, scrutiny, search, separation, study, subdivision, test.

So analysis is done by analysts. And what exactly does an analyst do? Once he or she has identified an area of interest, there is the process of collecting, cleansing, integrating and organizing relevant data – tagging it as necessary and navigating it. Then there will be the need to find and select documents in search for specific content; summarizing and abstracting when needed. And once there is enough useful data to operate on, there will be sorting, collating, comparing, computing, tracking, linking, relating, trending and slicing and dicing in order to forecast and predict. Then there will be the need to present the data in ways that allow meaning to jump out, through crosstabs, graphs, maps and dashboards. Lastly, there is the most important step in the process: interpreting the results. If this is not done correctly, all the previous work is wasted and useless.

If all this sounds like a fair amount of effort, it’s because it is. Analysis in a sense entails pursuit. There is a problem, an issue, something we need to take action on – and we have to tackle it intellectually and do our best to define, delimit and then make recommendations on courses of action. Most analysis takes place through the process of hypothesis testing. When presented with a problem or an issue, we start to develop hypotheses as to what the reasons for the problem are. And then we must do analysis on each hypothesis until we can disprove it and start on another one, or until we prove it and then proceed to determine a recommendation on how to solve the problem.

But you cannot be a true analyst unless you are possessed by some level of mental curiosity. There has to be that intellectual drive to dig into things, to solve problems, to find answers. Some of us are born with it, but in others it has to be instilled, nudged, nurtured. And this is where culture comes in, especially in public sector organizations.

In the private sector, the profit motive is a powerful engine for problem solving that is constantly pushing for answers through analysis. That has been one of the big drivers of business intelligence as a discipline.

For example, if McDonald’s learns that sales were significantly down in New England last month, it won’t just cross its arms and forget about it. This can have major implications for its stock price, pressures from the franchisees, and obviously, impact on the careers of corporate executives. So what happens? Analysis. There will be an investigation to determine why sales were down, and this means looking at the data. Hypotheses may emerge around a number of variables: weather, prices, competition, seasonality, etc. And this is where analysis allows the enterprise to pin down what specific reason, or combination of reasons, were the cause of the shortfall. Analysts may look at the sales data across states, cities or zip codes to see if the problem was localized or general; product sales analysis may point to Big Macs or Quarter Pounders; seasonality analysis may indicate that school vacations may have been a factor. And this is driven by the corporate need to find an answer to the issue in order to fix it.

In government, there is often a different attitude toward problems. If customs revenue collections were down last month, for example, there may not be a major outcry within the Department of Homeland Security that runs the Customs and Border Protection (CBP) component. Their job, they may argue, is primarily to keep the country safe – not raising money for the Federal treasury. There probably won’t be a significant inquiry coming from Congress as to the reason for the shortfall. Yet we might be facing a situation that has nothing to do with fewer goods coming in that have tariffs imposed on them, and has a lot to do with operational inefficiencies, personnel mismanagement, technology malfunctions or a combination of these. We won’t know unless the situation is analyzed, and that will be driven by individuals with mental curiosity…and a culture that rewards analysis.
(By the way, I do not mean to pick on CBP, this is a totally fabricated example.)

Public sector agencies very often need to work at ensuring that their corporate cultures establish a high value on, and properly reward, that push toward analysis – that mental curiosity that makes an individual investigate further, not be satisfied with unanswered questions – and nurture the urge to always look for ways to do things better. That challenge of moving our government agencies to espouse and nurture a culture of analysis falls squarely on our leaders. Let us hope that we elect and appoint leaders that are up to the task.

  • Dr. Ramon BarquinDr. Ramon Barquin

    Dr. Barquin is the President of Barquin International, a consulting firm, since 1994. He specializes in developing information systems strategies, particularly data warehousing, customer relationship management, business intelligence and knowledge management, for public and private sector enterprises. He has consulted for the U.S. Military, many government agencies and international governments and corporations.

    He had a long career in IBM with over 20 years covering both technical assignments and corporate management, including overseas postings and responsibilities. Afterwards he served as president of the Washington Consulting Group, where he had direct oversight for major U.S. Federal Government contracts.

    Dr. Barquin was elected a National Academy of Public Administration (NAPA) Fellow in 2012. He serves on the Cybersecurity Subcommittee of the Department of Homeland Security’s Data Privacy and Integrity Advisory Committee; is a Board Member of the Center for Internet Security and a member of the Steering Committee for the American Council for Technology-Industry Advisory Council’s (ACT-IAC) Quadrennial Government Technology Review Committee. He was also the co-founder and first president of The Data Warehousing Institute, and president of the Computer Ethics Institute. His PhD is from MIT. 

    Dr. Barquin can be reached at rbarquin@barquin.com.

    Editor's note: More articles from Dr. Barquin are available in the BeyeNETWORK's Government Channel


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Posted February 2, 2009 by Anonymous

Hi Ramon -- I agree that today, most analysis is done by analysts. That's one of the main reasons for the low penetration of BI into companies, particularly midsize companies. You need to be an analyst to do the analysis, and most companies don't have many analysts, if any. Analytic applications are the way to address this issue. It doesn't meant that analysts will go away, but that you will be able to get analytic insight to help you do your job without being an analyst. Real analytic apps need several things to be effective, not just a prebuilt data model. Since the users aren't analysts, analytic apps need to include the questions that people should be / need to be asking about their area of business. It also needs to provide a way to help people interpret the results (even as a service provided by the vendor, which is becoming a more common solution to the problem that companies don't have analysts in house). Then a sales manager can be shown what types of deals they're most likely to win so they'll know where to focus. A marketing manager can easily be shown the combination of campaigns that works best. A finance manager can see trends in where their revenue is coming from. Only when we move from tools that must be used by analysts to analytic apps that are designed for business users will BI be able to live up to its full potential to help companies be more efficient and more effective.

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