For many organizations the use of data analysis tools, analytics programs, or BI software is…
While Analytics and Business Intelligence systems have been consistently listed at the top of CIOs’ prioritized spending lists in Gartner’s annual CIO surveys over the past eight years, it’s surprising how few enterprises are looking beyond merely gleaning insights from data rather than what they need to make effective decisions.
Gartner also reported that during the past decade, “organizations have spent over $60 billion on Business Intelligence software and service efforts to improve business performance, yet many have failed to achieve significant benefits, or at least have found it hard to quantify the benefits.” (from Gartner report “Use Analytic Business Processes to Drive Business Performance, May 25, 2016”) Clearly, giving business users access to information and “insights” isn’t enough. This further suggests that businesses would benefit by having better mechanisms to plug information derived from analytics systems right back into their businesses to make that information actionable and valuable.
While most enterprises have embraced transactional business processes to improve the efficiency of their operations, they have not applied similar processes to their analytics systems. As a result, many routine decisions, like a price offer to a specific customer, are made on-the-fly without the benefit of detailed analysis. However, the basic analytic framework within their companies could be enhanced to greatly assist such decisions.
Today, most business analytic processes are somewhat primitive. In many cases, they follow the course of: A) Observe data, B) Determine if anything unusual pops out that requires further action, C) Look around further for any additional “insights,” D) Deal with any unusual results in an ad-hoc manner, E) The end.
Or the processes are so confusing and inefficient as to no longer resemble repeatable processes. These follow the path of: A) Compile spreadsheets from 50 managers, B) Consolidate them manually since they’re fundamentally incompatible, C) Distribute the error-laden results back to the business, D) Repeat every quarter regardless of tangible results.
Sound familiar? Fortunately, there is a solution with the emergence of decision-making platforms, which provide a framework for users to follow prescribed decision-making processes. Beyond just assembling and analyzing data, these systems turn the results of those analyses into actionable business decisions. They do this through organized steps that are repeatable, efficient and auditable. Structured decision-making processes can be used to transform the operations of the entire enterprise, from finance to HR to manufacturing and strategic planning.
Analytic business processes deliver more than just the efficiencies of forcing users to follow prescribed sets of actions; they are a means to embed expert knowledge into an organization about HOW to be more effective. The analytic process contains the optimal decision-making steps to follow to achieve the best decision possible.
As an example, let’s consider the buying decisions of a typical fashion retailer, which relies on the ability of its buyers to spot and exploit the hottest trends. Typically, there are a few truly outstanding buyers who consistently pick the right merchandise while the rest of the buyers have mixed success. Careful observation shows that the best buyers are the most adept at leveraging the information and analytic tools at their disposal.
We also see that they perform the same series of analytic steps each week to help them pick new merchandise. In doing so, they have created their own analytic process. Now imagine the positive impact on the company when the other buyers on the team can use that same decision-making process, in an easy to follow series of steps? That’s the idea.
It’s important to note that the best analytic processes often come from decision-makers themselves, not necessarily from a central authority. The processes often grow organically, based on trial and error and continuously improve over time. So it’s equally important that the technology supporting these processes is simple and flexible and allows those same decision makers to easily build and modify these processes.
These same concepts apply to many other types of business decisions. There will always be a certain percentage of decision-makers who embrace and apply information and analytic tools better than their peers. If the goal of your Business Intelligence software is simply to provide “insights,” it will remain useful to only the small population of users with the incentive, knowledge and aptitude to discover and capitalize on these insights.
In this manner, analytic processes allow organizations to harness the knowledge and insights from their best decision-makers and apply it to the rest of the organization in a systematic manner. If you’re looking to see greater engagement and return from your Business Intelligence investments, implementing analytic processes is a great place to start.