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One of the community groups to which I donate my time is an organization that puts on a Concours d’Élegance – a vintage car show. Such Concours date back to seventeenth-century France, when wealthy aristocrats gathered to see who had the best carriages and most beaudacious horses. Our Concours serves as the centerpiece to a broader mission of raising money for several charities. There a many such events in the United States and elsewhere, but this one, which has been held every year since 1956, has the distinction of being the longest continuously running Concours in the United States.
A couple of years ago I started helping out on the day of the event, but soon I was in charge of registering and keeping track of the 250 or so cars that apply to be in the show. The spreadsheet-based system for keeping track of the cars was a mess, and it was the root cause of many (if not most) of the needless headaches that we were experiencing running the event. I wound up with the job because (following my own advice) I suggested that we change from spreadsheets to a real database, and I developed its design. At the same time we also changed from an all-paper registration system to an online one in order to reduce the need for volunteers to key in information from forms. This has substantially reduced errors associated with the data entry process. As a bonus, because we have all the information stored electronically, the members of the committee that selects the cars to appear now use tablets to review applicants rather than passing around paper forms and photographs.
The new system has streamlined many of our basic processes and cut down on errors, but it has not been without challenges. One is that owners of older cars tend to be older themselves, and some have limited or no experience using computers, and little or no interest in learning how to deal with email and the Internet. Even though we offer the option of filling out a paper entry form and attaching photographic prints, our notifications go out by email and the payment process is handled online. Like many businesses, we have had to determine how best to work with members of the public (car owners in our case) who find our process an exasperating headache.
Managing the registration process also provides ongoing confirmation of the research that my colleagues and I perform on using information technology in business. To be sure, the issues I confront are trivial in comparison to those of a larger organization and very different in scope. Yet I can see the connection between shortcomings in process design or software capabilities and some problems that develop on the day of the event. Here are some the lessons I have learned over the past two years, all of which reinforce the best practices Ventana Research advocates.
The quality of your IT department is a key factor in business success. Our research finds that companies with a competent IT staff get better results from IT than those that have mediocre or worse talent. In our Concours we found that to be true. To bring the registration online, we worked with a company that has an online scheduling service. The owner of the business is a Concours volunteer and a generous supporter. He donated the cost of his employees’ time, and we piggyback on his infrastructure. This works out well because his basic system was well suited to be modified to our very limited requirements.
The project involved creating a one-page web form that populated a couple of tables. I had defined all the fields in the tables along with their properties. We did not need the company to create and refine reports because we were linking Microsoft Access to the source tables and using it for reporting. We only needed the company to do the coding of our online form and create the underlying SQL tables.
We started developing the online registration system and database for keeping records two years ago in early November with the expectation that we would be ready for testing at the end of January. I thought this would give us plenty of time to begin accepting entries beginning in May. I figured the schedule was realistic, even though our project was a low priority for the staff because it was at most a one-week job. Unfortunately, the schedule turned out to be optimistic because the guy responsible for doing the work was incompetent. Instead of being ready in January, we went online with very limited testing in mid-June, three months late and six weeks after our announced starting date. While waiting, we had to constantly deal with owners who wanted to enter their cars. In the shortened registration process, we had to contend with a more concentrated load of questions, exceptions and errors. Despite all of the pain, I had to smile because our little project was almost a parody of the typical horror story of a major IT effort gone wrong. IT projects can fail for many reasons, but a competent, dedicated IT organization will overcome obstacles and promote business success.
Business leaders should be able to speak IT. Few business schools teach IT skills to prospective executives. Some businesses like to cross-train promising employees so that when they are promoted to senior-level positions they will have had the experience to understand most if not all of the facets of the business at an elemental level. They are in a better position to see how the issues in one part of the business affect things in others, and so are better able to deal with issues as they arise. Such experience also enables them to challenge excuses from people who are not getting the work done. In our case I can easily imagine being told the delay was the result of a change in scope, flawed software, negligent consultants – anything but the IT department staff. Line-of-business executives should know something about IT and IT department operations (or at least have someone on their staff who does). Without such knowledge, they will hear lame excuses that they don’t know enough to challenge, and have no ability to communicate clearly and quickly to overcome IT-related issues.
Bad data doubles workloads. OK, I made up that number, but I doubt it’s way off the mark. We collectively spend about half the time we spent two years ago collecting, correcting, organizing and using data about the cars and their owners. We are able to generate accurate, up-to-date reports in a matter of minutes. I fear that this lesson is often lost in corporate settings. Managers and executives often have only a limited idea of how much time is wasted in their organizations by needless and fixable issues. Good data stewardship is critical to the smooth functioning of all businesses, big and small, as I recently noted. Having good data yields a positive result: We were able to let the selection committee review the cars on tablets. This speeded up the process, and enabled members to easily jump back to compare entries and zoom in on photographs of cars and their engine compartments.
Root cause analysis and continuous improvement should be your mantra. We had many fewer issues in this our second year of operating the online system, but I still see improvements we could make to improve process efficiency and reduce the number of errors. When I find issues in our processes I try to determine their root cause. If it’s data- or technology-related, I try to figure out how to fix it. If it’s a process issue, I try to see whether an IT element might help the process along.
My major project for this coming year will be to deploy the Eclipse BIRT open source reporting tool for the Concours. We have users who need up-to-the-minute reports as we get close to the day of the event, and require write-back capability to correct database errors. I’m trying to follow our advice to use desktop spreadsheets where they are appropriate (and they are sometimes) but avoid them when they ultimately create more problems than they solve. A substantial portion of this year’s data issues started with desktop spreadsheets.
Sometimes a simple condition makes it easier to demonstrate larger principles that are at work in a more complex situation. In this case, keeping track of cars and their owners demonstrates the importance of using the right tools to efficiently achieve good data management. This example illustrates the importance of having the right people doing the job, and the importance of continually looking for root causes of business issues and finding ways to address them.
Robert Kugel – SVP Research
Our research consistently finds that defects in data are the root cause of a wide range of problems encountered by modern corporations. The magnitude of the problem correlates with the size of the company: Big companies have bigger headaches than midsize ones. Data issues diminish productivity in every part of a business as people struggle to correct errors or find workarounds. Issues with data are a man-made phenomenon, yet companies seem to treat bad data as some sort of force of nature like a tornado or earthquake – something that’s beyond their control to fix. At best they look for one-off workarounds and Band-Aids without tackling the root causes or recognizing the need to keep data issues in check. Data stewardship can and should be a part of a disciplined approach to management in the same way organizations implement quality control, cash management and legal compliance.
I recently gave a presentation at an analytics conference about using advanced analytics in the finance function. Advanced analytics includes techniques such as predictive analytics (a topic covered in depth by my colleague Tony Cosentino), simulation and optimization, which companies can use to make better-informed decisions, increase their awareness of positive or negative developments in their business and become more agile in responding to opportunities or threats. But advanced analytics – indeed any analytics – require that accurate data in the proper form and format be readily available.
Unfortunately, in almost all companies, data quality does not get the attention it needs and information management benchmark research found only 13 percent have completed data quality initiatives. (The exceptions include companies for which clean, accurate data is critical to their business model, such as web-based ones.) In most, no one is responsible for data and no serious ongoing programs for data stewardship and data governance. There is no executive-level focus on relentlessly working to keep data clean the way that, say, defect-free production might have. Like the weather, people complain about data but no one really does anything about it.
In every organization, management expects the data people use to be accurate and accessible, but we find that remarkably little is done to ensure this. Companies must address two broad issues before they can improve their data environment. Most obviously, they must have the right processes and tools in place to eliminate the root causes of bad data and deal with data quality remediation efficiently. But the other issue is people-oriented. Who’s responsible for good data? In most organizations the answer is “nobody,” or if it is somebody the person has neither the authority nor the tools to do much about data quality. Corporate leadership must keep attention focused on the value of data quality to the smooth operation of the business. The organization has to accept the idea that the issue is important and that a solution to the problem exists. Even as I write this, though, I wonder to what extent this sort of change is possible. They don’t teach data quality in MBA programs.
The trend toward big data puts a spotlight on data quality management. Without quality data, as I’ve noted, organizations will wind up with just a bigger, less manageable version of the garbage-in-garbage-out syndrome. Advanced analytics have the potential to give companies a sustainable competitive advantage, but this can’t happen if the analytics are built on data that is inaccurate, requires excessive amounts of grooming or is not timely enough to be commercially valuable. While automation plays a part in data management, attitudes and management are equally critical to improving the quality and timeliness of data.
Robert Kugel – SVP Research