Accenture Technology Vision 2013

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Trend 2. Design for Analytics Accenture Technology Vision 2013 The minimum mindset: data as a strategic asset Businesses have the right idea: data is a strategic asset. Data (good data) makes you smarter. A recent study of 179 companies, led by an economist at the MIT Sloan School of Management, suggests that companies that adopted “datadriven decision-making” have productivity levels 5 to 6 percent higher than can be explained by other factors, including investment i in technology. Savvy companies are working to discern more about transactions and events than ever before. They’re looking for context and ways to make the insights they gain actionable. They’re trying to understand not only what happened but why. And, when did it happen What transpired before it happened What transpired afterward It could be a purchasing scenario that reveals the associated items that customers buy. But it could also be a failed online purchase. Did someone get a coupon from Starbucks but go next door to Dunkin’ Donuts anyway The desire to get these answers is why companies are investing so heavily in big data, business intelligence, and reporting tools. The fact that they are still investing means that they haven’t yet found the solution, even though so much technology is available. Companies need to start looking for the solution to the problem a different way. Quantifying the world around us When enterprises don’t have access to the right data, they need to start looking differently at how they go about getting data. Companies can’t rely solely on the limited universe of data that they already have. The focus now needs to shift to quantifying the enterprise: capturing the actions, interactions, and attributes of the employees and processes that make an enterprise tick. They must step out of the box and formulate the right questions that will help the business make strategic decisions. The data that’s necessary will become evident. The challenge, then, will be figuring out not only how to collect it, but, in many cases, how to create it. Many software vendors are already starting to make it easier for enterprises to tackle this challenge. Third parties are increasingly creating Application Program Interfaces to 22
Trend 2. Design for Analytics Accenture Technology Vision 2013 “ When enterprises don’t have access to the right data, they need to start looking differently at how they go about getting data. Companies can’t rely solely on the limited universe of data that they already have. ” allow data to be more easily extracted from software products, including packaged software applications. This further puts the onus on companies to figure out what data they should be gathering from their systems to answer the company’s broader questions. Companies are also increasingly adding instrumentation to their custom applications, designing them to collect and report transactions, activities, or logs. For instance, to help improve its recommendations engine, Netflix tracks how customers interact with on-demand film downloads. It looks at metrics such as when customers pause the movie and what scenes they watch ii over again. In another example, to continuously improve the quality and effectiveness of its online class materials, Knewton incorporates the ability to track specific data about how students use its software. It tracks not only how long it takes students to complete an assignment and their ultimate score but also their keystrokes, how long it took them to answer individual questions, and if they stopped in the middle of an assignment or question. “We're physically collecting thousands of data points per student per day,” said iii founder and CEO Jose Ferreira. Companies are also looking to the blossoming of sensor technology to fill data gaps as they arise. This technology represents a way to create and collect information from physical environments and devices that today represent blind spots in a company’s data portfolio. Research company Strategy Analytics predicts that cellular machine-to-machine (M2M) connections necessary to transport the data from distributed sensors to the data center will grow from 277 million in 2012 to 2.5 iv billion by 2020. The companies that have already defined their top-level strategic questions are striking first. Many companies in logistics, transportation, and energy, for instance, have already clearly defined their need to track the movement of goods and the usage of power. UPS has developed a system of in-vehicle sensors and handheld computers to track information not only about its shipments but also about its trucks’ movements. This is what helped it determine that making left turns slowed deliveries and increased fuel costs as a result of idling; it used the information to create routes that minimized left turns, saving the company 9 v million gallons of gas annually. In addition, knowing when trucks are going to reach their destinations helps UPS’s employees ensure that there are sufficient resources to load 23
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