Solve the Right Problem by Tying Analytics to Operational Processes

Analyst Viewpoint

For decades analytics tools have been focused on solving the wrong problem. They’ve been designed to make it easier for business analysts to do ad hoc analyses on behalf of others, instead of enabling business users to perform their own analysis. There will always be a place for ad hoc analyses, but organizations can better meet their day-to-day analytic needs with more directed, purpose-built analytical applications that are embedded into operational processes. Line-of-business personnel want to get their jobs done as quickly and effectively as possible, so organizations should seek to empower them. These individuals shouldn’t have to become analytics experts or application programmers.

Pre-built analyses help avoid the Achilles heel of analytics: data preparation.

Analyses that are pre-built and embedded into business processes provide many benefits. Decisions can be made much more quickly, and they are made more quickly for several reasons. Obviously, if the analyses are pre-built, they are immediately available. But perhaps more importantly, pre-built analyses help avoid the Achilles heel of analytics: data preparation. Data preparation slows down analytic processes dramatically. Our research shows that more than two-thirds of organizations (69%) identify it as the most time-consuming part of the analytics process. If the data is prepared as part of the pre-built analytical applications, it saves the line-of-business functions from performing this time-consuming task.

Our research shows that organizations recognize the value of embedding analytics into their operational processes. Nearly three-quarters (73%) indicate this is important or very important. Both business (71%) and IT personnel (77%) recognize this importance in nearly equal proportions. Not only can the line of business access analytics more quickly, but these pre-built applications also provide greater governance over the process which is often the responsibility of IT. Since the analyses are pre-built and approved for deployment to the workforce, the organization can also be assured that there is consistency in the way the information is being accessed and analyzed.

Analytics can be embedded into many processes. Participants in our research included 23 different areas or processes when asked to identify the top five where data and analytics were most important to their organization. In sales operations, most organizations have standard pipeline analyses that should be easily accessible to the field and regional sales management. In manufacturing, production and quality metrics can be pre-defined and embedded into operations. Customer service and call center metrics embedded into operational processes can ensure the consistency and quality of the customer experience.

With the recognition of the value of analytics embedded into operational processes, organizations must determine how to create and deploy those applications. The key is how to inject domain knowledge of the specific business processes into applications without requiring business analysts to become application programmers. These applications also need to be designed to be easy to use with a compelling user experience. Using a business intelligence platform with “no-code” application development capabilities often provides the best approach. Business analysts can combine analyses to support specific processes via point-and-click interfaces with the platform handling the underlying work necessary to package and deploy the applications.

Business intelligence platforms provide several benefits in this scenario. As noted above, they can eliminate the need to write any programming code, but where necessary they can offer the option to extend the application with custom code or scripting. In addition, analytics platforms support many different types of analyses and visualizations, thus reducing or eliminating much of the work that would be necessary to assemble these applications using individual components. These platforms also generally provide broader capabilities than other application platforms that are not specifically designed for analytics. In situations where additional analyses are needed beyond what has been pre-built, the platform and resources skilled in its use can be used to extend existing analyses or create custom analyses or applications from the same data sets. Using a platform also provides a robust deployment architecture that can scale, is governed properly, and can be monitored and managed without any additional development effort.

It’s time to deliver analytics that support the organization’s business processes directly. Don’t leave the analyses to ad hoc processes and chance. Empower your workforce by making it easier and faster to access the analytics they need to perform their daily responsibilities and do their jobs better. Find and implement a business intelligence platform that supports application development and deployment. The organization will be more agile and responsive to existing business requirements and new market requirements as they arise.