5 Insights for Executives

Insights for 5executives Predictive analytics The C-suite’s shortcut to the business of tomorrow Of special interest to Chief executive officer Chief financial officer Chief marketing or sales officer Chief information officer

In the era of big data, companies across a range of industries are recognizing the need for • Finding and accelerating growth opportunities — drawing on internal and external data to better intelligence and insight about their business. They want to work out how to make the best help model and predict business outcomes, identify the most profitable opportunities and decisions, drawing on the right information, at the right time. differentiate the business from its rivals. One organization that has been pioneering in its use of predictive analytics has been the United • Improving business performance — enabling agile planning, more accurate forecasting, better States Postal Service. Using an analytical approach, it predicted which workers’ compensation budgeting and trusted decision-making support. claims and payments were unwarranted — and saved some US$9.5 million during 2012 alone. This • Managing risk and regulatory pressures — improving reporting processes through the is not an isolated example: many leading organizations have started to regard their information as exploitation of more robust data, while also identifying potential risk areas, such as compliance a corporate asset. violations, fraud or reputational damage. Business benefit can be gained by creating systems that can convert information into actionable • Exploiting emerging technologies — continually identifying new opportunities to gain insights insights, all within the context of key business priorities. Some of these include: from data. 2 | 5 Insights for executives

What’s the issue? Very few companies are fully exploiting the potential of predictive analytics. And At the outset, issues range from working out how to derive benefits from these new aspirations also often collide with the struggle to contain and cut IT spend. information and in which context such data might be relevant. There is also a The key questions start with the ability to quantify the value of available need to prioritize those activities, not least as views may differ sharply between information within the context of an organization, a department or business what IT considers important versus what the rest of the business does. Finally, function — working out which data sources might help to strengthen the there is the challenge of determining how to perform and operationalize generation of new insights. analytics, while taking the impact on processes and behaviors into account. Why now? We operate in a digital world, with vast — and constantly increasing — volumes of Predictive analytics is not brand new, but the technologies that help firms make data being generated. Every minute of the day, more than 200 million emails are sense of their data have only recently become available. This is allowing firms to sent globally, while Google receives more than 2 million search queries. The retailer uncover and exploit patterns in their historical data, identifying both risks and Walmart now handles about 1 million transactions every hour, adding to a database opportunities ahead. In short, businesses can use data to look forward, rather that is nearly 2.5 petabytes in size. By 2020, some 450 billion online transactions than at past performance. are expected to take place every day. Sources of data, both structured and Leading organizations increasingly recognize that predictive analytics can deliver unstructured, are multiplying rapidly, from external social networking interactions more than just customer insight; it can also have a positive impact on compliance, to internal call center transcripts. Indeed, organizations now embrace data as a security, fraud detection and risk management. fourth factor of production, alongside capital, people and materials. They use it to help sharpen their business performance by differentiating their offerings, uncovering new opportunities and minimizing their risk exposure. Predictive analytics is not brand new, but the technologies that help firms make sense of their data have only recently become available. 5 Insights for executives | 3

How does it affect you? Many businesses report a disconnect between their desire to capitalize on data and their ability to do so. It becomes even more imperative for business and IT to Efficient analytics-enabled business processing develop a joint model and terminology for valuing information, which is directly linked to the organization’s key performance indicators. measurably impacts performance. Efficient analytics-enabled business processing measurably impacts performance by supporting better planning, forecasting and decision-making. It can help boost revenues, reduce risks and increase agility. But getting this right often demands Ensuring that all parts of the business are engaged, so that the full picture is that traditional IT and operational roles, structures and culture adapt to a new captured and information gaps are minimized, is another challenge. Customer way of working, not least through the introduction of specialist positions, such as data is a typical example: sales holds some data, such as billing addresses and data scientists. transaction records, while marketing may hold customer feedback insights, and The adoption of analytics also brings with it new risks. Traditional levels of logistics holds physical delivery details. Information is often either duplicated or comfort around data quality, privacy, intellectual property and reputation inconsistent, if it is available at all. management must evolve. This, in turn, impacts people’s behavior. Nevertheless, correctly navigating such challenges is worth the effort. In an era of consumerization, those organizations able to monitor and predict customer behavior and preferences closely, without crossing the line on privacy, can gain significant advantage. 4 | 5 Insights for executives

What’s the fix? Bringing technology-driven analytics to bear on a project involves several As such steps become embedded, a portfolio of analytics projects should be key steps: developed. Quite simply, with limited resources, the most important initiatives need to be pushed to the front. As part of this, an implementation roadmap needs to be set out that also charts the likely impacts a given project might have. 1. 2. Understand the problem and Collect the information needed address it in a way that it becomes to tackle the problem. This demands clear which insights need to be an analysis of which data is most discovered through predictive needed, what is already available and analytics. where any key gaps lie, along with an assessment of data quality and a sense of where missing data might be sourced. 4. 3. Act on the findings — even if they Perform the analytics, using imply a major shift — by adapting mathematical algorithms to help processes and behaviors to capitalize uncover patterns within the data. fully on the transformative potential These findings need to be translated of predictive analytics. back to the business problem to help interpret the outcomes in the most useful context. 5 Insights for executives | 5

What’s the bottom line? The information war has already started. From here on in, business performance More specifically, information-led companies will be able to sharpen their will depend to a great extent on an organization’s ability to gain access to the competitive edge. There are numerous examples of what this might deliver: right information and to exploit it fully. attracting more valuable and loyal customers, charging prices closer to the • At a high level, predictive analytics can help companies to: market rate, ensuring more focused and relevant marketing campaigns, running more-efficient and less-risky supply chains, ensuring the best product or service • Move from a retroactive and intuitive decision-making process to a proactive quality levels, ensuring highly individualized customer service and guaranteeing a data-driven one deep understanding of how process performance drives financial performance. • Build models that more closely predict future real-world scenarios and their related problems and opportunities • Uncover hidden patterns and relationships in the firm’s data 6 | 5 Insights for executives

Want to learn more? The answers in this issue are supplied by: Drazen Nikolic Robert Hirt EMEIA Leader Director Enterprise Intelligence, Enterprise Intelligence, EMEIA Advisory Center EMEIA Advisory Center Ernst & Young AG Ernst & Young LLP + 49 89 14331 19481 + 44 20 7951 4086 [email protected] [email protected] Torsten Kiewert Executive Director Enterprise Intelligence, EMEIA Advisory Center Ernst & Young AG + 49 89 14331 13974 [email protected] For related thought leadership, visit www.ey.com 5 Insights for executives | 7

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