6 Best Practices for Successful Business Intelligence

2015-09-23_12-40_410.pngBusiness intelligence (BI) is not about technology. No doubt there is much technology involved, but a sound business intelligence strategy concentrates more on methods. The outcome of intelligence gleaned from a strategic reporting or decision support system should be an action or decision. The decisions made from business intelligence will likely lead to changes made in strategy and/or individual business process.

These changes in strategy and business processes will necessitate changes to one's enterprise resource planning (ERP) or other transactional systems. For example, new business rules or codes may need to be added to the ERP in order to operationalize a decision that was made. This will require an understanding of the business rules engine of the ERP as well as the implications from a historical measurement perspective of changing or adding codes to the system. People will need to be trained and constituents may need to be informed of new rules.

BI is much more about organizational alignment or people and processes around a common set of strategies and goals then it is about technology. To that end, follow these 6 best practices to move your organization from silo-based planning to one that is aligned around a culture of evidence:

  1. Define areas for exploration – What subject areas need to be studied? Not all can be effectively studied at one time – not at the start – therefore, you will need to prioritize. The organizations leaders will need to set the priorities based on the key strategies that need to be affected.
  2. Articulate problem statements – Now you have identified the subject areas to be studied. What are the problems in that area? Simple year-over-year trend analysis will often highlight where the problems are lurking. The problem should be stated as follows: [Subject Area] is down by 15% compared to last year.
  3. Identify causal factors – Perhaps one of the most overlooked steps in the process. Your problem statements only tell you what is happening. It is critical that you find out why it is happening. Statistical models need to be employed to determine the key drivers influencing the problem area. Identification of the key drivers in the area will help you isolate the problem and determine the factors causing the problem.
  4. Determine corrective action – Once the causal factors have been identified decisions can be made and corrective action taken. True evidence-based decision making.
  5. Align people, process, and technology – Decisions inevitably lead to change. Most often the change comes in the form of a new business process. The new business process will need to be codified in the ERP system and people may need to be reorganized and/or retrained. This will be the hardest step in the process toward a culture of evidence, yet it is also the most critical.
  6. Measure outcomes – Now that people, process, and technology has been aligned to solve the problem, you must measure the effectiveness of this action. Be careful that you allow a sufficient amount of time for the impact of the change. In fact, decision makers should agree about the length of time they will permit for the action to take hold and pre-determine a point in time for re-evaluation.

As you can see from the diagram above, the process is cyclical. As decisions are made and corrective action is taken, key drivers will change. This will constantly cause the organization to reevaluate and revisit its strategies and tactics over the course of time.