Television reality shows today feature a wide range of human activity, normal and otherwise. One particularly interesting show, "Hoarders," profiles people "whose inability to let go of their belongings is so out of control that they are on the verge of personal disaster," according to the A&E Network website.
Unfortunately, many business leaders engage in similar hoarding behavior, albeit with data rather than personal possessions. Companies are trying to determine what to do with all the data accumulated and warehoused in electronic versions of the overstuffed garages seen on the TV show.
Beginning in the 1970s, the combination of technology advances and the advent of the 'Consumer Revolution' produced a wave of technology and data capabilities. The result was the development of large systems focused on transaction-level information, theoretically designed to manage businesses and processes. So far, so good. But to make such systems behave in an integrated way, companies had to figure out where to keep the information, so they turned to data warehousing -- collecting the bits and bytes of data generated from such systems to store for a rainy day.
Now, however, as collection and reporting technologies have become widespread, companies are awash in data from internal and external sources, but they are severely challenged in their efforts to use that data to make well-informed decisions. In general, the pace of progress around the generation and reporting of data has far outstripped the pace of progress around analysis and "so-what" usage of the information.
Faced with ever-increasing virtual mounds of data while coping with legacy systems and an IT investment cycle that is often out of sync with the pace of business, many companies find themselves adding layers of complexity rather than creating real insight and value. Instead of collecting and organizing data to effectively improve things like product development, customer retention and satisfaction and pricing, among other areas, companies are hoarding data and hoping to find a use for it at some time in the future. It's not uncommon to find that a company has thousands of applications producing unusably large numbers of reports and outputs.
To bring order to the chaos generated by too much data, it's useful to apply five organizing principles:
- Don't listen to what I say; watch what I do. When asked what they might buy in the future, or what product features are most important, most customers actually predict different outcomes from what they actually do when observed "in the act" later. This is why companies who get analytics right will win.
- History is for professors. The (near) future is for business. Experience shows that looking at what customers are doing now is the best predictor of near-future behavior. Looking at historical trends is often misleading. Figure out which data and insights are needed for better customer interactions and more profitable business operations in the next six months.
- A dictatorship makes for a bad political system but it's a reasonably workable IT strategy. A good IT governance process sets clear priorities and helps the organization make investments that maximize the return of the product portfolio. The IT governance process and team not only guide project delivery, they help others understand the processes and the IT solutions that have been built, helping train users to get full potential from the tools installed.
- Not all data is created equal. Companies should focus more on identifying the data that is really relevant to make internal managerial decisions. This is a two-step process: First, define which data is really relevant from the transactional system, and which generate irrelevant data; and second, define analytics, metrics and key performance indicators to support forecasting.
- The milestone isn't the thing; delivering the project is only the beginning. Once a project is completed and the system is rolled out, it is essential to maximize ROI for as long as possible. IT teams should review opportunities that new versions will add and upgrade them periodically, adding life to the investment and reducing the overall support cost.
Companies have been focused on making sure they have as much data available as possible. This approach does not contribute to day-to-day operating efficiency, nor does it help executives make informed decisions.
For example, while most companies base their reporting on "historic" data, not many companies use predictive reporting yet -- but they will. Through the use of customer analytics, companies can improve their understanding of their customers' behavior. Using data to look forward, rather than backward, gives companies the opportunity to go where their customers are going rather than where they have been.
Matthew Reilly, a managing director in Accenture Management Consulting, oversees the Process & Innovation Performance service line. He focuses on helping companies streamline their processes to help them manage complexity, and add more rigor to their innovation processes, thereby contributing to operational excellence. Ronald Michnowicz, another executive in Accenture's Process & Innovation Performance service line, helped research this article. Accenture is a management consulting, technology services and outsourcing company.