1. Analytics drivenUsing analytics to help gain a competitiveedge in manufacturingIntroduction For example, how well can you answer questions, such as:Data, data everywhere, and not enough time to think. Like • What really drives value for our customers?the sailors on Coleridge’s mythical sea adventure, many • Which of our customers are profitable to serve?manufacturing executives find themselves surrounded by • How do our customers view us compared to therising waves of data. But where are the hidden treasures — competition?those golden nuggets of information needed to optimize • What investments drive the highest returns?margins? More than ever, rapidly evolving technology has • Who the high potential performers are in ourbecome the albatross around the manufacturing decision organization?maker’s neck. • Where are we likely to experience safety problems? • Do we have information needed to answer importantOver the last decade, many manufacturers have made questions?significant investments in their information technologyinfrastructure. With such systems in place, executives are More and more, manufacturing executives areexpecting and needing shorter response times. Given the increasing their focus on analytics for the answers. Newcurrent realities in manufacturing, several tough questions advancements in analytics can provide not only reportsneed answering, such as: on past and present operations, but also help forecast the• How much can adjustments in one or more key future — giving progressive manufacturers the competitive performance areas affect us? edge.• Which course of action is the most worthwhile?• Are we getting the advantage we expected from our IT investments?In a recent Deloitte Dbriefs webcast survey, 20 percentof polled participants reported that they viewed theiranalytic capabilities as strong in certain domains. Moreencouraging, another 17 percent responded that dataanalytics is becoming an everyday need across theenterprise.1Becoming analytics driven requires a fundamental shiftin global business operations. This starts with knowingwhich questions to ask — the crunchy questions — thathelp manufacturers build the foundation for their analyticsinitiatives. By asking the right questions, you can revealthe most relevant data and the most valuable insights.Deloitte is working with many clients to identify the priorityquestions — those often unanswered but critical inquiriesthat — when answered — evoke “ah-ha!” moments.1 T. Hanley, L. Dittmar, T. Leatherberry (June 2011); Deloitte Dbrief:Using analytics to gain a competitive edge in manufacturing.As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for adetailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rulesand regulations of public accounting.
2. Setting the stage Pricing based on data analytics can be particularly Increased pressure on margins and a global supply beneficial to the global supply chain — the manufacturer’s chain are just two of the key challenges facing today’s worldwide capabilities. More than ever, manufacturers manufacturers. Such business objectives are driving the should focus on their suppliers’ reliability both at the local need to harness the power of the information stored in IT and national levels. This means managing relationships systems. with many countries, understanding the impact of their regulations, and identifying the cost of basic storage, Data analytics provides an opportunity for the logistics, and other expenses related to doing business. manufacturer to look upstream into the global supply chain and downstream into the consumer base to Many manufacturers are also struggling with labor better anticipate what the customer will need in the shortages in critical workforce areas, such as engineering, future. Similar to retail, customer loyalty and establishing science, and technology. Data analytics can help by long-term relationships are growing in importance for giving insight in the increasingly important arena of talent manufacturers. In the article, “Know What Your Customers management, as well as foresight into employment and Want Before They Do,” the authors explain how retailers wage growth rates, thus helping manufacturers meet their can use advanced data analytics to “target customized personnel needs. offers at the right place in the right moment across the right channel” and thus increase the chances of marketing The key to getting better answers involves leveraging success by nailing the “next best offer” (NBO).2 As the enterprise information management, business intelligence, manufacturer’s ability to capture and analyze highly and advanced analytics together to get a 360-degree view granular data improves, targeted offers, or NBOs, become of the organization. Once in balance, the competitive more possible and offer a competitive advantage for early advantage revolves around a better-integrated supply adoptees. chain, a stronger focus on customer relationships, and new insight into the product life cycle. Data analytics can also be applied in the area of manufacturer pricing to improve profitability. With Same story, new twist analytics, manufacturers can begin to better understand not only what, but how and why various factors impact Analytics Increasing business advantage the bottom line. Information about downstream customers Simulation and modeling Advanced that can be valuable to pricing and product placement analytics and sophistication Quantitative analysis can be relatively basic and easily acquired. For example, information, such as age, gender, number of children, Advanced forecasting residential address, income or assets, and psychographic Role-based performance metrics lifestyle and behavior data can be easily acquired and very Exception and alerts Basic telling of what pricing is suited to a particular region or business Slice and dice queries and drill downs intelligence market. Management reporting The convergence of exploding data volumes, new data sources, powerful new technology, and other factors has caused the need for more and better analytic capabilities. “Nothing new, totally Until now, manufacturers have focused mostly on basic reporting, and but more and more are using sophisticatedrevolutionary” tools and methods to go deeper. In addition to being able to more effectively and efficiently report on what happened, analytics provides the ability to answer important questions: • Why it happened, • What will happen next, • What will happen if, and • What is the most significant outcome for business 2 Tom Davenport, John Lucker, Leandro Dalle Mule (2011, optimization December); Know What Your Customers Want Before They Do. Harvard Business Review. 2
3. The business case can be made — and our experience“Perhaps the most important shows that high-quality analytics investments can be actually self-funding. Concerns about data quality, whilecultural trend today: The explosion often justified, are typically addressable and sometimes merely serve as excuses for not moving forward. Leadershipof data about every aspect of our itself is the key ingredient to moving forward, overcoming the inertia of silos, motivating the team, and setting theworld and the rise of applied math vision for the future. Clarity on both the opportunities and the risks of not acting is essential.gurus who know how to use it.” Trends in the driver’s seat Powerful trends are driving the adoption of new— Chris Anderson, editor-in-chief of Wired approaches to business analytics and an overall increase Investments today are paving the way for more predictive in the demand for analytic capabilities. A convergence of and prescriptive analytics. While experience is still a critical forces and factors are making business analytics pervasive factor in effective decision making, manufacturers can no across multiple industries and sectors. It is not a narrow longer rely on experience, “gut feel” and intuition alone. pocket; it is not in just some parts of the world; it’s The harsh business reality is the need for an increasing everywhere — and manufacturing by far is no exception. focus on data and the analysis of that data. This shift marks a significant change and possibly the most important Key factors driving today’s business need for more effective culture trend today. The crunchy question here is, “Do you data analysis include: think or do you know?” If you know, then where’s the data • Exponentially increasing amounts of data, including “Big to support your decision? Data” • An aggressive regulatory environment Overcoming barriers • Increased pressures on profitable growth Many organizations are still early in their journeys to • The quest for new signals and hidden insights develop fact-based cultures and to put in place new capabilities that can effectively and efficiently turn data With these business drivers in mind, manufacturers need into new, insightful information. In our experience, most deeper insights into the risks of not being in compliance business leaders understand the inherent value of using with new laws and regulations and the ability to be high-quality information and analytic insights to improve increasingly responsive to the public and other types of operations and drive smarter decisions. But even when stakeholders. Particularly in the manufacturing sector — there is clear recognition of the potential, companies with the supply chain becoming increasingly complex and sometimes fall short of achieving the capabilities they want the competition being global in nature — it’s a tough and need. game. There’s little room for era or assumptions. Lacking the level of information management automation Do you think or do you know? and analytic tools they desire, these companies make do Manufacturers also need to be aware of new signals, with manual processes and fragmented solutions, working which come from other types of data sources like social outside of the existing enterprise systems. There may media and other unstructured data that is not found be pockets of analytics innovation, but what we often in traditional systems. With the application of new encounter is a sea of spreadsheets. techniques, new tools, and better capabilities, insights that have been hidden are coming to light. The good news is Why is this happening when the benefits of improved today’s technology can meet challenges of answering the information management and enhanced analytic why and substantiating the facts. capabilities seem clear? Deloitte has identified a variety of barriers that companies face when trying to become more Linking analytics to high-impact areas proficient with analytics across the enterprise: A full-scale shift toward analytics is underway today in • Lack of a compelling business case virtually every domain of the manufacturing company. • Concerns about quality of data From product design to customer relations, finance, • Organizational silos risk, supplier and partner management, and sales and • Insufficient executive sponsorship marketing — every facet of the manufacturing operation • Acceptance of current state is on a quest for more specific and accessible information. 3
4. No area is more relevant than another. In fact, an effective The rise of analytics in manufacturingdata analytics initiative requires symbiosis amongst Given the current demands on manufacturing, there is nodivisions. single “best place” to start improving data analytics. Most CFOs still tend to be the driving catalysts for implementingThe opportunities, needs, and drivers may vary in a analytics initiatives. During the Dbriefs webcast,particular organization; however, the overall goal remains participants reported that supply chain, customer relations,the same — a search for better analytic capabilities across production, and risk management would benefit fromeach and every one of these domains or functions. So if improvements in data analytics.you are thinking that maybe there is just one place wherethis happens, that wouldn’t be true. “So what are the business issues driving data analytics in manufacturing?” Product design, supply chain, pricing,The more challenging issues focus on pricing and customer, and service are all critical performance areas.profitability, commodity volatility, and endeavoring toprovide product safety in the global supply chain. The For example, R&D data historically has been isolatedexpanding global economy has turned a once siloed view from the actual manufacturing process. By paying moreof the world into the necessity for a 360-degree view attention to this data with their next wave of productsbeyond the four walls of the manufacturing entity. and services, companies can significantly reduce time to market, better define their client niche, and improveThe high-impact areas tend to define the basis of the overall production quality. “Unstructured data” from“crunchy questions,” and thus dictate what kind of data is social networks and blogs can provide a wealth of suchneeded. Questions, such as: information to gain insights on customer wants and• How do I deal with external data into my architectural needs that translate into advancement of products. As a framework? result, many manufactures are trying to build a continuous• How can I better understand what actions have occurred learning environment around R&D. to improve the overall function of the organization?• How do I stack up compared with what other companies Data analytics in supply chain involves an understanding of are doing? the volatility occurring across the demand channel. Today’s supply chain is “multi-channeled” with a particular focus onMost manufacturers are still in the experimental phase of looking downstream from the manufacturer to the retailer.data analytics. Not any one company is doing everything Data analytics can help bring insight into the supply chainwell or “has arrived” and is done. Business leaders process by:typically desire to have information quickly, so answers • Aiding in demand forecasting and supply chain planningare instant. But it’s not just a simple reporting matter. • Integrating data from multiple sources, includingAdvanced analytics uses data mining capabilities to unearth retailers, customers, R&D, and inventory datauncommon insights, such as the risks of supplier failure and • Developing macroeconomic models to more effectivelythe future of products. predict prices Most manufacturing companies have invested heavily in improving supply chain management. However, recently Market/sales Product developed tools are designed to provide a means to better management management exploit supplier and supply chain information. Manufacturing companies can realize additional improvements around their efficiency by driving analytics into their operations and pulling multiple data sets together. Supplier/partner Analytics Customer management management Combined with design and supply chain, value-based pricing and cost analytics provide an understanding of how production costs affect the bottom line. Effective pricing cannot be sustained without the supporting analytics. Enterprise Service Manufacturers are continuously challenged with delivering management management products that attract new customers while maintaining their loyal base. Thus, loyalty analytics programs are no longer just a retail issue. 4
5. Because of the rapid pace of product development, • Targets: Deloitte can help identify and refine thecustomer service is becoming a key differentiating factor capabilities it needs. Focus is important. We will bringamongst manufacturers. Tied to customer focus, many a demonstrated framework for exploring, categorizing,companies are looking at how do they integrate service rationalizing, and prioritizing reporting and analyticsinformation into product design, which involves leveraging needs.R&D data to anticipate the ever-changing consumer base.Thus, no area is isolated in manufacturing data analytics; • Technology: While technology is certainly not the entirethe key is pulling it all together. solution, it is important to recognize that the “right” technology — properly designed, deployed and used —DELTTA: Elements for effective analytics is essential. An effective analytics program cannot existDeloitte has worked with Tom Davenport — an without leveraging modern tools.internationally recognized expert on analytics—to helpclients understand how to become analytics driven. As • Analysts: Of course, an effective analytics initiativepart of this collaboration, we have extended Tom’s requires highly skilled, experienced analysts. Here we willwork to include critical elements in an effective analytics help identify the skills and experience it needs to exploitprogram. The goal is to effectively embed analytics into the power of analytics.an organization’s systems and culture so that value canbe realized at various levels of the business. This new Pulling it togetherDELTTA (Data, Enterprise, Leadership, Targets, Technology, Despite cross-enterprise demands, barriers can still existand Analysts) Model is designed to help guide change to implement an effective analytics strategy or program.management plans and activities: During the Dbriefs webcast, slightly more than 24 percent of the participants expressed concerns about quality of• Data: Solid analytical decision making requires access data, while more than 20 percent also cited organizational to usable and actionable data. Collecting, accessing, silos as significant barriers. In addition to data quality and and drawing insight from such data also necessitates silos, stumbling blocks also included lack of a solid business corporate consensus on business metrics and strategy. case, insufficient executive sponsorship, and management’s Deloitte has the experience needed to help reach such satisfaction with the current state. All of these issues consensus, to clean data where needed, and to converge are decreasing in importance, indicating a trend toward silos of data located in disparate systems so that it is increased interest in analytics. In our poll, the largest accessible across the enterprise when and where it is percentage, 33 percent chose “all of the above” as biggest needed. barrier. Clearly, undertaking improvements in analytics capabilities across an enterprise is not an easy undertaking.• Enterprise: Whether it is data, tools, or people, Deloitte takes an enterprise approach to analytics. This requires Getting started on the analytics journey requires starting examining all areas of the organization for answers to where you are and knowing where you currently are on those crunchy questions that help drive strategic business the journey. Highly fragmented organizations typically direction. This affects data governance and application struggle the most in getting started, but it’s a recursive architecture decisions. And it fits precisely with the process no matter where you need to begin. Today’s recognition of the need to integrate data from across business objective in data analytics will ultimately become multiple functions and groups. tomorrow’s new beginning.• Leadership: Although enterprise-wide involvement is A good starting point is often a place of pain where the essential to an effective analytics initiative, corporate benefits of implementing a data analytics initiative can be leadership — or sponsorship — is just as critical. Visible obviously seen. Success leads to success, and the focus is and persistent leadership support will be essential to on being value driven. Once established, data analytics can analytics’ initiatives. Deloitte has experience working be built outward through the organization. with leaders at various levels of the organization to get analytical decision-making initiatives underway and to keep them on track. 5