科爾尼（A.T. Kearney）：2018年全球企業數據分析影響力指數（英文版）（12頁）.pdf

1、1 The Untapped Value of Analytics A new global benchmarking study reveals that analytics leaders see 60 percent more profits than the laggards. 1The Untapped Value of Analytics The growing availability of data combined with expanded connectivity and amplified computational power are creating an unpr

2、ecedented opportunity for businesses to use analytics to improve their decision-making. As a result, companies around the world are spending billions of dollars a year to build their analytics capabilities, hoping to use smart technologies to tap into the power of data. In an environment marked by t

3、ough competition and a data explosion, most C-suite executives are unaware of the best practices and are left wrestling with an array of questions. How does our analytics capability compare with our regional and global peers? Which business areas will see the most value? Is the organizational struct

4、ure designed to maximize the impact, and do we have the right talent? Is the budget big enough? And most importantly, is there a sufficient impact on the bottom line to justify the required investments? With this in mind, Melbourne Business School and A.T. Kearney have created the Analytics Impact I

5、ndex to determine analytics potential impact on a companys profitability and identify the areas that hold the largest opportunities for improvement. Based on our study of hundreds of companies around the world, the Index pinpoints the impact on the bottom line and the capabilities needed to extract

6、the most value. Our research reveals that analytics leadersonly 8 percent of companiessee 60 percent more profits than laggards do. Although most discussions about analytics are focused on technology and infrastructure, our study shows that leadership and the organizational culture have the potentia

7、l to extract the most value. The leading organizations typically have a well-defined analytics strategy and a culture of data-driven decision-making that is embedded across the organization. However, companies that invest in data ecosystems without any strategic leadership could actually see a negat

8、ive impact in the short to medium term. The inaugural Analytics Impact Index provides a framework for measuring both the maturity and the impact of analytics. Forward-thinking companies can use the Index to identify the gaps and the potential opportunitiesbuilding the case for change. Over time, the

9、 Index can be used to gain a comprehensive view of a companys analytics capability as it evolves. In this paper, we discuss the Analytics Impact Index and take an in-depth look at the stages of maturity, the potential financial impact, and the strategies companies can put in place to move up the mat

10、urity curve to become analytics leaders. The Analytics Impact Index Many companies are using analytics to try to uncover meaningful patterns in their data applying disciplines such as statistics, optimization, simulation, visualization, and machine learning in an attempt to develop data-driven decis

11、ion-making. The question is how effective are these initiatives? To answer this question, other researchers have focused on analytics maturity. For example, one study shows how marketing analytics can impact performance outcomes, and another resulted in a framework that encompasses all dimensions of

12、 a companys analytical maturity.1 A.T. Kearneys first analytics assessment, the Leadership Excellence in Analytic Practices study, was launched in 2014 to evaluate the opportunities and challenges that companies face. However, it focused on a specific area of analytics and did not address the impact

13、 of analytics. 1 “Performance Implications of Deploying Marketing Analytics,” International Journal of Research in Marketing, volume 30, issue 2, June 2013; “A Business Analytics Capability Framework,” Australasian Journal of Information Systems, volume 19, 2015 2The Untapped Value of Analytics Now,

14、 for the first time, the Analytics Impact Index gives organizations an understanding of the potential of analytics as well as the capabilities required to capture the most value. To create the Index, Melbourne Business School and A.T. Kearney surveyed more than 400 companies with a median revenue of

15、 $1 billion across 34 countries and a dozen industriesbenchmarking both the value realized and the analytics capabilities within each organization (see figure 1). We then analyzed the financial impact.2 2018 Analytics Impact Index Sources: Melbourne Business School; A.T.Kearney analysis Figure 1 The

16、 Analytics Impact Index covers a broad range of companies Industry coverageExecutives 12 industries Top three: Consumer goods and services: 21% Technology: 14% Healthcare: 14% More than 400 respondents C-suite: 43% Directors: 17% Managers: 28% Median revenue: $1 billion Revenue range: $1.5 million t

17、o $247 billion Company size Americas 15% Europe, the Middle East, and Africa 23% Asia Pacific 62% The Analytics Impact Index highlights the difference in a companys profitability based on two factors: maturity in terms of the analytics operating model and the impact of analytics as a proportion of t

18、otal profits. Our study reveals that only 8 percent of companies are extracting the full potential of analytics after calculating the level of analytics maturity (see figure 2 on page 3).3 Firms across the four stages of maturity have varying analytics capabilities: Laggards. Analytics is limited to

19、 descriptive analysis of the data, and generally backward-looking reporting on performance. These companies do not yet have a clearly defined analytics strategy and lack the culture needed to move forward. 2 This research and analysis were carried out between January and July 2018. 3 Because this st

20、udy is in its first year, these inferences are largely correlational rather than causal. However, as we obtain longitudinal data with periodic surveys, we hope to determine causation from various factors. 3The Untapped Value of Analytics Analytics stages of excellence Sources: Melbourne Business Sch

21、ool; A.T.Kearney analysis Figure 2 Four stages of analytics maturity 10% Laggards Followers Explorers Leaders 46% 36% 8% Followers. Analytics is used to diagnose what drives business outcomes, especially cost and revenue. However, analytics is not used strategically to optimize business decisions, a

22、nd there is no broad analytics culture driven by top management. Explorers. Analytics is used to optimize business performance by diagnosing and predicting business outcomes. Although there is an analytics strategy, the analytics culture is not well-developed across the organization. Leaders. The bi

23、ggest difference between leaders and laggards is the C-suite commitment, the strategic alignment between the business and the analytics strategy, and the right culture. Leaders integrate analytics into all decisions to generate foresight about relevant trends and fuel successful business outcomes. R

24、eal-time analytics help drive innovation and create a competitive advantage. To assess a firms analytics maturity, we use a framework of four dimensions (see figure 3). Sources: Melbourne Business School; A.T.Kearney analysis Figure 3 Analytics maturity can be measured in four dimensions Strategy an

25、d leadership Culture and governance Talent and skillsData ecosystem 4The Untapped Value of Analytics Strategy and leadership. This dimension, which is the domain of the leaders, looks at who within the company is driving analytics and in what direction the company is headedfrom understanding the req

26、uired elements to creating a road map that aligns with the overall business strategy to drive value. Culture and governance. This dimension is about the operating structure and processes and the companys general attitude toward analytics. Are the right organization structure and governing bodies in

27、place? Can the company implement change? Is the organization analytics-driven? Data ecosystem. This dimension, which tends to be the focus for laggards, is about having the right technological infrastructure and data management framework. We define data management as the development and execution of

28、 architectures, policies, practices, and procedures that properly manage a companys full data life-cycle needs. Talent and skills. This dimension is about recruiting the right people with the right skills and retaining, developing, rewarding, and using them effectively. It also measures the level of

29、 sophistication of the analytics models and the quality of the insights. What we found is that companies at the lowest stage of maturitythe laggardshad 60 percent lower profits than the leaders (see figure 4). Evolving from laggard to follower can be a long process that requires making large investm

30、ents into the necessary resources and infrastructure. For followers, it is difficult to feel the momentum because so much potential remains untapped and many investments have yet to deliver significant returns. However, as companies move along the maturity curve and into explorer territory, they beg

31、in to capture significant benefits and very quickly start seeing the value of analytics. But what does this mean for leaders? Are they extracting the full potential of analytics with nowhere to improve? Our research indicates the leaders are redefining the boundaries of analyticscreating their own p

32、ath and widening the gap from the laggards. Next, we take a closer look at the two factors that make up the Index: maturity and impact. Potential increase in profits Note: Potential refers to the increase in profit if a company were to increase its maturity to level 4 at the current point in time. S

33、ources: Melbourne Business School; A.T.Kearney analysis Figure 4 Laggards can see significant gains in profits if they embrace analytics Laggards Followers Explorers Leaders +55% +15% +60% 5The Untapped Value of Analytics An In-Depth Look at Analytics Maturity Measuring analytics maturity provides a

34、 benchmark against industry and regional leaders and sheds light on the areas where a company can improve. Strategy and leadership Only 33 percent of laggards have a clearly defined analytics strategy compared with 86 percent of the leaders. Unlike explorers and leaders, the laggards and followers a

35、ppear to be struggling to establish a road map and understand the elements needed to reach their vision. Although better than laggards and followers, explorers and leaders struggle the most with tracking key performance indicators and monitoring their successes compared with any of the other dimensi

36、ons. Although some of the laggards and followers do have executive-level sponsorship, they are not championing analytics as effectively as explorers and leaders (see figure 5). Considering that 67 percent of laggards do not have a strategy, it is no surprise that 58 percent do not have a clearly def

37、ined data leader. Who leads the data and analytics team? Note: Numbers may not resolve because of rounding. Sources: Melbourne Business School; A.T. Kearney analysis Figure 5 In leading organizations, analytics has a C-suite presence C-suite executive Chief data oficer or chief analytics oficer Dire

38、ctor or vice president No clearly defined lead Team leader or senior manager 25% 58% 17% Laggards 21% 11% 36% 9% 23% Followers 20% 41% 15% 25% Leaders 21% 17% 15% 46% Explorers 2% Culture and governance All leaders have a defined analytics organization, which is not the case for the other stages. In

39、 fact, 67 percent of laggards and 15 percent of followers have no defined structure (see figure 6 on page 6). Most explorers and leaders have some form of central data and analytics organization. Across all stages, creating an analytics culture and aligning teams around a common goal is a major stru

40、ggle, but the main difference between the laggards and the leaders is how willing they are to take a risk by experimentingtesting the boundaries and looking for ways to extract value in targeted areas. Rather than taking calculated risks in high-potential areas, the laggards wait for others to explo

41、re uncharted territory. 6The Untapped Value of Analytics Talents and skills Leaders balance the hiring and development of internal talent with the use of external partners. With skilled in-house talent, leaders create and maintain the analytics culture more effectively than laggards and better manag

42、e their external partners. Interestingly, leaders and explorers show the most sophistication around deploying analytics to increase the number of customers whereas laggards and followers focus on sophistication around sales. Furthermore, unlike explorers and leaders, laggards and followers do not of

43、fer company-wide analytics training because they rely on their partners for their analytics capability. Data ecosystem Leaders use real-time data and sophisticated tools, programs, and platforms while laggards tend to invest more in data ecosystems. Leaders greatest strength is in maintaining their

44、data warehouse, which lays the foundation for optimal analytics. On average, leaders make their data much more accessible across the organization than laggards do. Our study also shows that technology without direction can have a negative impact on profitability, especially in the short term. Analyt

45、ics organization structure Sources: Melbourne Business School; A.T.Kearney analysis Figure 6 Firms that struggle with analytics lack a central analytics organization Model Decision-makingEnterprisewide coordination Coordination across business units Business unit level only Ownership Global big data

46、 and analytics organization with full ownership Global big data and analytics organization for oversight Local big data and analytics organization Strategy definition and execution Globally defined and globally implemented Globally defined and locally implemented Locally defined and locally implemen

47、ted Business unit Analytics Business unit Analytics Business unit Analytics Center-led, locally executed Centralized Federated Not defined Laggards 11% 22% 67% Followers 15% 34% 30% 21% Leaders 43% 29% 29% Center-led, locally executedCentralizedFederated Explorers 50% 21% 24% 6% 7The Untapped Value

48、of Analytics The Financial Impact of Analytics To measure the financial impact of analytics, the Index calculates the proportion of profit that is attributable to analytics while indicating the maximum improvement opportunity. The impact is determined by assessing the profitability difference across

49、 firms, controlling for factors such as geography, industry, company size, and inherent company factors. Not surprisingly, a higher stage of maturity is associated with a greater financial impactand the impact is exponential (see figure 7). There is a slight decrease in the average impact for followers, potentially because of the lag in results after the initial investment in analytics. The variability in the upper end of impact is much larger at a higher stage of maturity because of the wealth of opportunities that analytics brings once the foundation has