Predicting the future of predictive analytics. December 2013



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Predicting the future of predictive analytics December 2013

Executive Summary Organizations are now exploring the possibilities of using historical data to exploit growth opportunities The proliferation of data and the increasing awareness of the potential to gain valuable insight and a competitive advantage from that information are driving organizations to place data at the heart of their corporate strategy. Consumers regularly benefit from predictive analytics, in the form of anything from weather forecasts to insurance premiums. Organizations are now exploring the possibilities of using historical data to exploit growth opportunities and minimize business risks, a field known as predictive analytics. SAP commissioned Loudhouse to conduct primary research among business decision-makers in UK and US organizations to understand their attitudes to and experiences of predictive analytics, as well as a future view of usage, value and investment. The research reveals that businesses are struggling to take full advantage of the burgeoning and already overwhelming amount of data being collected. Challenges abound as firms seek to make effective use of data. While many businesses are investing in predictive analytics and already seeing benefits in a number of areas, even more see this as a future investment priority for their business. The research points to a data-driven future where advanced predictive analytics sits at the core of the business function rather than being siloed, is embraced by a greater proportion of the workforce and is used to drive decision-making across the whole business. To achieve this future vision, however, it is clear that businesses need to up-skill their workforce and invest in more intuitive technology. While firms in the UK and US recognize the potential of predictive analytics and the need for investment in skills, the US is further along the adoption curve than the UK. US organizations show greater promise for future investment in and roll-out of predictive analytics software across the workforce. Furthermore, US organizations perceive fewer challenges in using data to inform corporate strategy, and sense a greater need for training to embed the benefits of the technology into day-to-day business. Loudhouse 2013 2

Key findings The current predictive analytics landscape Most (92%) say that the volume of data that their organization collects or has access to has increased in the last 12 months Three in five (61%) agree that predictive analytics is currently an investment priority in their organization, and most though more so in the US than in the UK think that it will be an investment priority in their organization within five years time (69% in the UK/78% in the US) Two-thirds (69%) say that predictive analytics is more about exploiting opportunities, with a third (31%) stating that it is more about minimizing risk. However, US firms (88%) are more likely than their UK counterparts (77%) to agree that effective use of predictive analytics minimizes business risk Those in the UK are more likely than their US counterparts to cite challenges of using data such as a lack of resource or time (47%/37%), too much data (46%/34%), lack of useful data (36%/23%), and unstructured content (32%/17%) This is also true for challenges of predictive analytics: cost of investment (49%/33%), a need for specialist skills (45%/35%) and data security concerns (39%/19%). Uncertainty around ROI is a greater concern in the US (23%/33%) The impact of predictive analytics The vast majority (85%) of those currently using predictive analytics report it having had a positive impact on their business Sales (46%), finance (44%) and marketing (42%) are the three functions seen to currently benefit most from the use of predictive analytics The key benefits of using predictive analytics are considered to be better business performance in the future (61%), greater insight into business dynamics (50%) and making greater use of data already available (49%) Organizations using predictive analytics in the US are more likely than their UK counterparts to report having gained a competitive advantage due to its use (66%/88%) Key to statistics: Grey: Combined UK/US data Red: UK data Blue: US data 3

Looking to the future Organizations using predictive analytics report that, on average, over a quarter of their workforce (28%) regularly uses predictive analytics software directly, and they would like this to rise in five years time to an average of 37% in the UK and 47% in the US For the optimal use of predictive analytics, the majority (68%) say that the business as a whole should be driving it US firms (87%) are more likely than those in the UK (81%) to agree that their organization would benefit from training in the future in order to interpret and apply predictive analytics in dayto-day business Predicting customer needs (80%/90%) and market trends (78%/90%) are seen to be valuable scenarios for which to use predictive analytics, more so by US than UK organizations With 90% of all of the world s data having been generated in the last two years, it is not surprising that organizations on both sides of the Atlantic are feeling somewhat overwhelmed by the sheer scale of the data challenge that they face. As data has proliferated, so technology vendors have responded by creating more advanced solutions to help organizations make sense of this data and use it to drive their business decisions. The field of predictive analytics holds great promise in helping organizations navigate an ever-changing business and customer landscape. By putting data at the center of organizational strategy, and ensuring that appropriate skills and technology are in place, businesses in both the UK and US will be well placed to steer their organizations to future success. Research Methodology 309 online interviews were conducted with business decision-makers with some responsibility for / input into overall company strategy. All had some knowledge of predictive analytics and worked in organizations with 50 or more employees. 153 interviews were conducted in the UK and 156 took place in the US across the following three verticals: Retail, Consumer Products, and Financial Services. Interviews were carried out in the UK and US during June-August 2013. Research was conducted by Loudhouse, an independent research agency based in London, England. 4

United States Overview of Findings The current predictive analytics landscape Data-driven decision-making is becoming increasingly integral to US business strategy. As shown in Figure 1, 62% agree that predictive analytics is currently an investment priority in their organization, with 78% expecting it to be a priority within five years time. The increasing availability of data means that businesses have the power to explore new possibilities. Over twothirds (71%) believe predictive analytics is more about exploring new opportunities, rather than minimizing risk (29%). Nevertheless, 88% agree that the effective use of predictive analytics minimizes business risk. Despite vast swathes of information being available to businesses, interpreting data into actionable insight is a difficult task. 94% say that the volume of data their organization collects or has access to has increased in the last 12 months. As such, 37% admit they lack the necessary resources and time to utilize such information, and a third (34%) say there is just too much data to analyze. Achieving ROI is of particular concern to US organizations, with a third (33%) citing uncertainty around ROI as a significant challenge to using predictive analytics. Figure 1. Levels of agreement with statements about investment and risk Predictive analytics is currently an investment priority in my organization I think that predictive analytics will be an investment priority in my organization within five years The effective use of predictive analytics minimizes business risk 62% 78% 88% 5

The impact of predictive analytics The vast majority (94%) of organizations using predictive analytics confirm it has had a positive impact on their business and, as such, its priority within the business is growing. For US businesses at least, much of their data-driven success is attributed to external-facing departments responsible for driving growth: sales (52%) and marketing (48%) are functions seen to currently benefit most from predictive analytics (See Figure 2). By having the right data tools, organizations are well positioned to drive their business forward. Nearly twothirds (64%) believe better future business performance is a key benefit of a predictive analytics strategy, with maximizing use of available data (47%) and greater insight into business dynamics (46%) also of value. Fundamentally, however, businesses using predictive analytics are able to translate insight into commercial success: 88% of companies using predictive analytics report having gained a competitive advantage as a result. Figure 2. Business functions currently benefiting the most from the use of predictive analytics in your organization (Base: Organizations using predictive analytics) Sales Marketing Finance Manufacture / production Supply chain management Senior management / Board Procurement R&D Human resources Don t know 1% 17% 15% 12% 10% 7% 25% 52% 48% 42% Other No business functions 1% 1% 6

Looking to the future It is clear that US organizations see predictive analytics playing a critical role in the future success of their business. Among businesses using predictive analytics, there is a desire for half (47%) of their workforce to be using such tools regularly by 2018 (See Figure 3). Yet the challenge for businesses is to ensure that their increasingly datacentric workforce has the skills to turn insight into action. 87% agree their organization would benefit from training in order to interpret and apply predictive analytics in day-to-day business. Corporate structure is also a success factor, with predictive analytics not being driven from silos or specialists but, instead, originating from the business as a whole. Two-thirds (67%) say that the business should be driving predictive analytics if it is to be truly optimized. If this is to be put into practice, employees will need user-friendly tools that blend the power of insight with ease of use and actionable outcomes. Figure 3. Average proportion of workforce directly using predictive analytics (i.e. using the software or interpreting/applying the output) Proportion of workforce currently using predictive analytics 29% Proportion of workforce would like to see using predictive analytics in five years time 47% 7

United Kingdom Overview of Findings The current predictive analytics landscape Big data has endowed businesses with a wealth of information. The vast majority (89%) of UK businesses state that the volume of data their organization collects or has access to has increased over the last 12 months. Rather than being seen as a preemptive tool to remove the uncertainty of the future, predictive analytics is seen to harness the power of opportunity. Two-thirds (68%) believe predictive analytics is more about exploiting opportunities, with the remaining third (32%) stating it is more about minimizing risk (See Figure 4). Figure 4. Is predictive analytics more about exploiting opportunities or minimizing risk? 32% Turning raw and often complex data into actionable insight is an enormous challenge, particularly for UK organizations. As shown in Figure 5, lack of resource and time (47%), too much data (46%) and lack of valuable data (36%) are the most significant problems facing businesses when using data to help inform business decisions. Part of the challenge is integrating data into an organization s way of thinking. Indeed, unstructured content (32%) and data not being viewed strategically by senior management (28%) present a further hurdle for UK businesses. Minimizing risk Exploiting opportunities 68% Adopting a predictive analytics program is also problematic. Beyond the cost of investment (49%), the need for specialist skills (45%) and data security concerns (39%) are secondary challenges holding back advanced business intelligence processes. 8

Figure 5. Challenges of using data to help inform decisions in the business Figure 6. Benefits of using predictive analytics Lack of resource / time 47% Better business performance in the future 58% Data located in disparate systems / locations 46% Greater insight into the business dynamics 54% Too much data 46% Make greater use of data already available 52% Lack of useful data 36% Knowledge & insight spread across more employees than just senior business analysts 49% Unstructured content 32% Improved profitability 44% Lack of / inadequate systems to analyze data 30% Increased operational efficiency 44% Big data not viewed sufficiently strategically by senior management 28% Driving business growth 41% High cost of storing and manipulating large data sets 27% Minimized risk 41% Difficulty translating data to drive action 26% Competitive differentiation 35% Cultural resistance to internal sharing of data 24% Finding / exploiting new markets and revenue streams 29% Not clear what we should actually measure 24% Increased customer satisfaction 28% Other 2% Driving innovation 27% There are no challenges 1% 9

Looking to the future The use of predictive analytics is set to grow as businesses acknowledge the organizational benefits that data-driven tools bring. Among UK businesses using predictive analytics, an average of a quarter (27%) of the workforce regularly uses the software directly, and they would like to see this rise to 37% within five years time. The impact of predictive analytics Despite these issues in adopting a successful data analytics strategy, three-quarters of organizations (76%) acknowledge the positive impact that predictive analytics has had on their business. Indeed, the key benefits of using predictive analytics are considered to be better business performance in the future (58%), greater insight into business dynamics (54%) and making greater use of data already available (52%) See Figure 6. In the UK, finance departments (47%) in particular see the greatest return from adopting predictive analytics, with sales (41%) and marketing (37%) functions also benefiting. While an array of business functions are seen to benefit, forecasting customer needs (80%) and market trends (78%) are the most valuable scenarios where predictive analytics can make the most significant contribution. Businesses must overcome a number of challenges if they are to fully realize the potential of predictive analytics in the future. Three-quarters (75%) agree that predictive analytics software would be difficult to use without employing a specialist, and 81% of companies feel they would benefit from training in the future in order to interpret predictive analytics in day-to-day business. As such, rather than relying on complex systems which requires extensive and specialist knowledge, businesses need tools which are intuitive and accessible for employees across an organization. For optimal use of predictive analytics, the majority (70%) believe that the business as a whole should be driving it. Organizations will only be truly successful in their endeavor to extract future forecasts from historical data once their users have the power to turn data into insight. 10

Conclusion Only once organizations harness the power of their data can they also gain greater control over the future. Alongside the recent explosion in the volume of data available to and collected by organizations, and the relatively recent ability to make sense of that data with a focus on the future, the next few years will prove interesting as predictive analytics enters the mainstream of business intelligence processes. Only once organizations harness the power of their data can they also gain greater control over the future. Businesses are struggling to take full advantage of the data at their disposal. Data volumes, structures and locations are causing a headache, and insufficient levels of resource and skill mean that it often remains a latent data opportunity. By and large, businesses acknowledge that predictive analytics holds significant potential for a multitude of purposes, both for exploiting opportunities and minimizing risks in future events. Those already using such data tools are gaining a competitive advantage, and the race is now on to harness data faster and more effectively than competitors. Firms on both sides of the Atlantic are planning to invest in advanced predictive analytics over the coming years. They expect it to become a business intelligence tool used by a greater proportion of the workforce compared to today. However, most recognize that in order to realize the potential of predictive analytics, it must be driven by the business as a whole, investment must be made in technology, and a workforce requires additional skills in order to interpret and apply analytics in day-to-day business. While data volumes and analytics skills shortages present challenges, opportunities exist for organizations willing to invest in solutions both in terms of skills and technology that will enable better visibility into, and thereby control of, the future. From impacting revenue growth to predicting marketing trends and customer needs, historical data holds the key to maximizing potential in the future. 11

More Information As market leader in enterprise application software, SAP (NYSE: SAP) helps companies of all sizes and industries run better. From back office to boardroom, warehouse to storefront, desktop to mobile device SAP empowers people and organizations to work together more efficiently and use business insight more effectively to stay ahead of the competition. SAP applications and services enable more than 183,000 customers (includes customers from the acquisition of Sybase) to operate profitably, adapt continuously, and grow sustainably. Organizations like yours can identify untapped opportunities and expose hidden risks buried inside vast amounts of data all in real time. You can design complex predictive models, visualize data from internal and external sources, and share insights across your ecosystem by harnessing the power of our predictive analytics solutions. Influence your business outcome in real-time and extract more value from your Big Data with predictive analytics from SAP. Our solutions can help you bring predictive insight to everyone in your organization across applications and mobile devices. Visualize the future: Spot trends, risks, and patterns hidden in your Big Data Run what-if scenarios and find the best possible outcomes in split seconds Act before it happens: Empower everyone in your business with predictive insight Loudhouse 2013 Learn more about SAP s Advanced Predictive Analytics Solutions at www.sap.com/predictive 12