SAG_Twitter_MEME_More_Data_Feb17.jpgHow can digital businesses move from “gut feelings” to fact-based decision making?

Decision making in the analog world fluctuates between two extremes: relying on the “gut feelings” of executives or relying on historic data contained in spreadsheets, financial statements and budgets. Gut feelings might have been adequate for the analog, non-real-time information world where a company could survive with single-digit growth — and had competitors who did the same. And intuition can be a valuable asset in the high-speed digital world, but — by itself — it is insufficient to explore the potential that Digital Enterprises provide.

Decision support systems must reflect the real-time nature of Digital Enterprises, particularly their capacity to respond instantly to changes and challenges in both their internal and external environments.  There are two major enterprise levels where decisions have to be made immediately: the management level and the operational level. Classic management decision support systems — the so-called business intelligence systems — focus on the aggregation of historical data. These systems are no longer sufficient in the digital world. Making business decisions by focusing on historical data is like driving a car by looking into the rearview mirror.

Today, businesses need to know what is happening now, so-called real time, for static data as well as for data-in-motion — today, even for mass-data-in-motion is possible.  On the operational level, employees can get ongoing support in real time, and not just based on historic facts. On an operational as well as on a managerial level, forward-looking decision can no longer be made looking backwards. For example, when a customer enters a shop, a clerk can have the necessary information to provide individual treatment — just as though the shopper was a long-term customer.

And innovation is moving on fast. The next step to real-time decision making is predictive decision making; that is, anticipating what will come rather than simply assessing what just happened.

Facebook receives around 300 million new photos every day from its nearly 2 billion users. These volumes of data are totally unprecedented. While you might expect a technology leader like Facebook to implement a sophisticated analytics infrastructure, how do you explain advanced analytics in sectors like water utilities and farming? TaKaDu, an Israeli company, helps water companies around the world monitor leakage. The water industry routinely loses 25–30% of its product in the process of delivering it. Theft and an outdated infrastructure are common leakage culprits. Unfortunately, neither problem is easy or inexpensive to monitor. Not surprisingly, then, the industry focuses on analytics that pinpoint the best payback areas. 

Moving to the agricultural industry, Climate Corp, a company started by Google alumni, provides crop insurance for farmers by analyzing 22 data sets of weather at a sub-zip code level every few hours, calculating roughly 10,000 scenarios that a grower could experience over the next two years. The company is leveraging 30 years of daily weather data and crop yields, among other data.

The advanced analytics described above provide a valuable snapshot of all kinds of business scenarios. Another new digital technology, complex event processing (CEP), provides the equivalent of a video for greater clarity. The financial services industry was an early adopter of CEP for trading algorithms and the capacity to identify patterns in fast-flowing data feeds. The industry now also utilizes CEP for pattern recognition to detect insider trading—for example, by correlating business events like earnings announcements with stock trades. In addition, many banks, including Singapore’s largest bank DBS, are adopting CEP on the consumer side of financial services for fraud detection.

Big Data analytics helps modern executives to take into account hundreds of parameters to predict with reasonable accuracy what will happen. Technology and a growing base of primary data, both structured and unstructured, are empowering a move to more fact-based decisions — and are an ideal complement to gut feelings.

Digital Transformation


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