It should be self-evident that organizations of all sizes and in all industries need to improve their processes and performance, but many have not adopted methods for optimizing improvement. Business analytics has the potential to fill this void and create high-performing organizations, if the focus is improvement of the competencies of people and processes using technology that can automate the steps of analysis.
I have seen organizations begin to advance efforts in analytics as the lines of business realize they must take responsibility for improvement and not expect IT to deliver what is needed. But unfortunately many have believed that business intelligence systems managed by IT would deliver sufficient insight on processes and performance. Such efforts have made strides in standardizing querying, reporting and delivery of information, but they cannot provide the analytic capabilities that line-of-business analysts and management require to make deeper improvement.
I have long insisted on the importance of IT to ensure the efficient processing of data and its consistency and quality to support business’ needs for analytics. Yet at the same time, the business needs to make clear its requirements for analytics and the flow of data between activities to ensure collaboration and sound decision-making.
This involvement might seem obvious, but it often is not done because it requires a re-examination of responsibilities and aligning actions and analytics to business purposes for driving improvement no matter where they are located in the business. Business also needs to have better foresight on the potential outcomes of business activities, which the use of predictive analytics built on modeling and deeper mathematics can supply; such tools have been available for some time but have not yet been widely adopted.
To benefit from predictive analytics requires preparation and focus on the right set of data and tools, as my colleague has pointed out (See: “Do You Have Predictive Analytics of “GIGO”?). It should also be noted that analytics usually require better computational efficiency from databases that support the tools that business people use. Business analytics also have capabilities to expand beyond data to unstructured content, text and speech that the organization encounters in interactions with customers and suppliers.
It is important to remember that you cannot take only a general approach to improving business analytics; you need to focus on the specific line of business and its needs, which vary from finance and human resources to the supply chain to marketing and sales, and to customer service and contact centers. Just as important is ensuring that the IT organization is focused on improving its own operations and applying analytics internally to do so. In all of these cases, a strong foundation of analytics can support improvement the key areas of people, processes, information and technology.
If you are trying to address your business analytics, I encourage you to participate in our latest benchmark research. What you learn from the results can help drive improvement in your organization.
Mark also blogs at VentanaResearch.com/blogs.