RESEARCH NOTE INCREASING PROFITABILITY WITH ANALYTICS IN MIDSIZE COMPANIES

Transcription

1 RESEARCH NOTE INCREASING PROFITABILITY WITH ANALYTICS IN MIDSIZE COMPANIES THE BOTTOM LINE Adoption of analytics such as business intelligence (BI), performance management (PM), and predictive analytics (PA) in midsize companies continues to lag behind that of larger organizations. Those that have embraced analytics are able to make smarter decisions using information rather than intuition alone. While there are common misperceptions about analytics in the midmarket, Nucleus has examined hundreds of analytics deployments over the past 5 years, including IBM customers, and found many midmarket organizations have gained benefits from analytics by overcoming these misperceptions. IBM Business Analytics includes the following capabilities: Business Intelligence (BI) includes reporting, ad hoc querying, dashboards visualizations, mobile access, and analysis Performance Management (PM) includes planning, forecasting, budgeting, what-if analysis Predictive Analytics (PA) includes statistical analysis, data mining, text mining and social media research. COMMON MISPERCEPTIONS AROUND ANALYTICS Small and midsize companies stand to make significant gains by adopting analytics applications such as BI, PM, and PA. Adopting multiple approaches often amplifies results. Unfortunately, too many companies fail to adopt due to misperceptions and doubts about the ease with which analytic technology can be deployed and used within the organization. The most common misperceptions include: Investing in analytics is too expensive. With limited IT resources, many small and midsize companies predict that even a modest analytics adoption is beyond their budgetary capacity and fail to even investigate their options. The perceived costs around software purchasing, hardware investments, complex licensing and deployment options, specialized IT skills, and extensive training seem too much to bear. Analytics environments are too complex. Companies often fear that they have too many data sources, applications and spreadsheets to bring together into a centrally managed analytics environment to make analytics tools practical, or fiscally viable. Nucleus Research Inc. 100 State Street Boston, MA Phone:

2 Analytics isn t required for improved decision making. Many VPs and executives of small and midsize companies feel that the collective wisdom and intuition of their employees is strong enough that data driven analytics won t meaningfully improve day-to-day operations, and the value from an analytics investment would not deliver significant decision making improvements, and thus limited business impact. THE TRUTH ABOUT ANALYTICS DISPELLING MISPERCEPTIONS Nucleus Research has examined a significant number of IBM Business Analytics deployments at companies of various sizes. Analysts compared the deployments of IBM Business Analytics at large enterprises with those at small and midsize companies in order to identify the traits, benefits, and best practices that characterize analytics deployments at smaller companies. Nucleus found that those that are able to overcome the common misperceptions and adopt analytics, are more profitable than those that did not adopt analytics. There are three facts Nucleus found, after performing in-depth examinations of analytic deployments, that decision makers should keep in mind: ANALYTICS ARE COST-EFFECTIVE Nucleus regularly performs in-depth examinations of analytics deployments and have found that deployment costs, including software, hardware, personnel, consulting, and training are well within the budgets of even small and midsize companies. Nucleus has also found that ongoing support costs are typically minimal, with the average deployment requiring less than a third of one IT administrator s time for support. Costs are also low relative to benefits, leading to high returns on investment. Some of the factors making analytics affordable include: Multiple pricing and deployment alternatives. IBM Business Analytics applications are streamlined to support the analytics needs of smaller organizations and packaged with lower per-seat costs that make the solutions more affordable. Nucleus has found that the average deal size for IBM Cognos Express, which provides integrated reporting, analysis and planning capabilities, is between $25,000 and $30,000 and spoke with one IBM Cognos Express user who said, When we shopped around, we were surprised that IBM Cognos Express came in at well under $50K. Other applications such as IBM SPSS Statistics, an ad hoc statistical and reporting solution, have flexible, low-cost packages that are easy to justify and allow organizations to add advanced analytics capabilities as they need them. IBM Business Analytics also offers cloud based solutions as additional lower cost alternatives for organizations to explore. Flexible deployment options. In examining deployments, Nucleus has found two ways vendors and users typically use to minimize software costs. First, not all analytics functionality is deployed at once. Small and midsize organizations can choose to adopt any combination of BI, PM, reporting, dashboards, visualizations, scorecards, mobile, planning, or predictive analytics, and keep the functionality as narrow as they Page 2

3 want in order to lower the costs. Second, costs can be lowered by deploying in stages. Nucleus has analyzed many deployments which began as narrow proof-ofconcept projects that were followed by a series of increasingly larger deployments as projects demonstrated ROI. At one company examined by Nucleus, the deployment team leader said, We caused analytics to catch on like a fad. We helped our sales people make better decisions and when folks from purchasing observed this, they wanted analytics too. By managing costs and publicizing deployment wins, analytics champions were able to convince internal decision makers of the value of analytics, enabling them to broaden their deployments. Reduced need for extensive training. In examining analytics applications and deployments, Nucleus has found vendors have minimized their customers training costs with improvements in the usability of the solutions. End users can build their own dashboards, visualizations, scorecards, plans, and reports, and as a result, vendors have minimized the amount of support required by IT departments. Empowering the business users with self-service, frees up IT to focus on strategic projects vs. providing routine analysis and reporting. The applications have become so intuitive that end users typically require little or no training in order to use the application. An analytics champion at a company examined by Nucleus stated that the cost was not an obstacle to adoption and said, Once we deployed, people learned how to use the applications on their own, so we didn t need to spend any money on formal training. Financing. To make it easier to adopt analytics, vendors such as IBM offer financing of both software and services so that upfront costs are not a barrier to adoption. MULTIPLE DATA SOURCE COMPLEXITY CAN BE MANAGED Vendors have also found ways to simplify analytics deployments by making it easy to integrate multiple data sources. For example, IBM Business Analytics includes functionality that uses metadata, which is data about data, to ensure that information from all data sources is properly interpreted and integrated into predictive models, reports, and dashboards. Nucleus found that data diversity is rarely an obstacle during deployments. With analytics tools that are designed to work with one another, such as IBM Cognos Express and IBM SPSS Statistics, the ability to leverage multiple analytic approaches does not mandate data transformation, eliminating a common barrier to entry for midsize organizations looking to apply multiple analytics techniques easily. At one company that earned a high ROI on its analytics investment, an IT director said, Data wasn t an issue. The consultants helped us build a data cube for each department on the deployment. Building each cube took less than a few weeks and our consulting bill was less than $30k. Nucleus has found that with so many cost-effective ways to manage data during analytics adoption, small and midsize companies are often able to integrate multiple data sources as diverse as flat files, spreadsheets, ERP, and CRM systems, financial applications, pointof-sales terminals, survey data and unstructured data such as social media feeds. Page 3

4 ANALYTICS IMPROVES DECISION MAKING Analytics improves the decision making of even the smartest and best-trained workforces. Although organizations have made significant investments in recruiting and training the best employees, many continue to underperform because of poor decision making. At most companies, employees routinely make important decisions with bottom-line impact on the basis of intuition or gut feel. Nucleus has found that when employees instead make fact-based decisions and use data from well-governed analytics applications, they are far more likely to make decisions that increase revenues, improve gross margins, and reduce operating costs. Greater agility and rapid insight into data for decision making enables companies to more quickly make decisions, and act on them with confidence. Organizations need to have confidence that sensitive data is governed with the appropriate security and controls, while knowing that they have a single version of the truth regardless of the diversity of the data sources. CUSTOMER EXAMPLES Nucleus has examined numerous deployments of analytics at small and midsize companies. Following are a few examples of deployments which generated high returns on investment and were well within the financial limitations of a small or midsize company. Nucleus found these companies followed a number of best practices that other companies can use to maximize the returns on their own investments in analytics. CITY OF LANCASTER The City of Lancaster, California, was incorporated in 1977 to provide citizens with a greater voice in local governmental services and policies and currently has a population of over 150,000. As one of 41 contracted cities under the Los Angeles County Sheriff s department, Lancaster wanted to provide guidance to ensure that deputies work as efficiently as possible. The city implemented IBM SPSS Modeler to analyze existing data and understand trends associated with Part I crimes (defined by Uniform Crime Reporting as murder and nonnegligent homicide, forcible rape, robbery, aggravated assault, burglary, motor vehicle theft, larceny-theft, and arson). Lancaster s data project took off when it continued to extend its data capture to include other sources of data and developed better models. Lancaster was able to quickly translate its existing data into models that were more accurate and useful, including a time-series analysis of crime going back to January The city was able to provide predictive models that maximized insight and allowed the creation of heat maps of crime throughout the city. THE TAKEAWAY Lancaster needed to gain greater visibility into where Part I crimes were occurring and where they were expected to occur in the near future. By hiring the correct resources, acquiring predictive and location-based analytics software, setting up the data Page 4

5 appropriately, and getting internal buy-in, Lancaster developed a new data-driven crime prevention model that helped reduce the crime rate by over 35 percent. The city created predictive models that accurately reflected its specific demographics, seasonal trends, and localized challenges. In addition, the City of Lancaster is commitment towards data analysis and a data-driven approach to augment the experience of law enforcement. By providing actionable heat maps that translated data into information that could be easily used, Lancaster was able to provide directional insight to both where crimes previously occurred and where they were expected to happen in the future. CONCEPT ONE Concept One is a provider of licensed accessories for men, women, and children. With an ERP system that had limited reporting capabilities, the company deployed IBM Cognos Express in order to both eliminate manual report building processes completed by the company s IS director and provide better operational data to managers. The deployment team first built a Microsoft SQL Server database populated with transactional data from the company s ERP system. After the database was integrated with IBM Cognos Express, existing reports were then replicated in order to automate the reporting process. Reduced costs were the primary result of Concept One s analytics adoption. By performing cost and benefit analyses on all of the company s design projects, the company found opportunities to eliminate projects and reduce designer headcount. Sales managers were also able to reduce costs. By using IBM Cognos Express to perform queries on each of the company s licensing agreements, they were able to determine which should be renewed and which should expire by obtaining extremely granular cost and revenue data for each agreement. After several years of better contract management, the sales department significantly increased both the company s revenues and its gross margin. THE TAKEAWAY Returns on investments in analytics can be increased by maximizing the availability of cost-related information. Although the project team was aware of managers business requirements for analytics during the deployment, the team could not anticipate all the analyses or decision making that would be made with IBM Cognos Express. In order to maximize the range of business decisions that could be improved with analytics, the team incorporated as many cost-related data sources as possible, including some data sets that had not been requested by the lines of business. The deployment team correctly anticipated that with an abundance of data, managers would entrepreneurially seek out and identify cost reduction opportunities, eventually reducing both operating costs and costs of goods sold. Concept One quickly realized an return on investment of 866%. Page 5

6 CINCINNATI ZOO The Cincinnati Zoo is a nonprofit 100-acre facility serving an average of 1.2 million people annually. The organization adopted IBM Cognos BI in order to give managers the information they needed to improve visitation rates, increase onsite purchases, and reduce costs. The deployment team first created a data warehouse consisting of point-of-sales data, geographic data, membership lists, and inventory records. The team then built 25 operational reports and dashboards based on the organization s operational and financial objectives. Adopting analytics led to more data-driven decision making by managers, higher revenues, and lower operating costs. Revenue increases were the result of improving managers abilities to examine the preferences and habits of visitors and members, leading to increases in membership volumes, ticket sales, and sales of food and merchandise. For example, after examining ice cream sales data, the organization determined peak sales times for this product and adjusted the opening hours of the ice cream kiosks, leading to higher revenues. By performing highly granular analyses of the organization s marketing efforts and results, managers also identified and eliminated ineffective initiatives and ad campaigns. THE TAKEAWAY Focusing on customers is one way to earn high returns on an analytics deployment. One reason the Cincinnati Zoo s adoption of analytics was so successful is that it was focused on helping managers learn about the zoo s customers: who they were, where they lived, why they visited, and what they purchased. This was achieved in two ways. First, every available customer-related data source was integrated with IBM Cognos BI. Second, the Zoo created a new and extremely rich data source by using point-of-sales terminals to get the zip code of a visitor during every onsite transaction. By gathering so much data on its visitors, the organization was able to learn more about the effectiveness of various ad campaigns and promotions. It also identified neighborhoods which were underrepresented in the zoo s visitor base, enabling the zoo to target its campaigns more effectively. CONCLUSION Nucleus finds that leaders of small and midsize companies can improve their operating results by overcoming the barriers of misperception and investing in business analytics solutions such as business intelligence, performance management, and predictive analytics. Analytic solutions can be cost effective to implement and several options exist to provide pricing and deployment options. Solutions are available, that manage multiple data sources, and metadata complexity in a cost effective manner. In addition, putting analytics in the hands of managers and employees and empowering the organization with the ability to make data-driven decisions, leaders can change their companies in three ways. First, they reduce the reliance on gut feel and intuition, allowing for better decisions Page 6

7 driven using data that improves outcomes by looking at all time horizons such as data from the past, the present and the predicted future state. Second, by improving employees decision making, they enable those employees with the insight and confidence to make decisions that increase revenue and reduce costs. And finally, by minimizing manual efforts for reporting and analysis, companies are able to improve productivity. Page 7