Business intelligence, and its increased availability and accessibility, has fundamentally altered decision making that in the past would have been based solely on intuition, anecdotes, and limited observation.
Business intelligence is a blanket term that refers to several activities which use raw data to make business predictions about consumer behavior. These activities can include data mining, online analytical processing, querying, and reporting. This data can be used to affect decision making, cut costs, and to take advantage of otherwise easy to miss opportunities.
Companies use this data to identify what parts of a business are in need of re-thinking, and which policies are performing as desired. The business intelligence tools of today are relatively streamlined and user friendly, so those on the business end can analyze data themselves, instead of always needing IT to run their own complex reports.
Business intelligence has been used for great advantage by a variety of companies and organizations.
For example, sports teams like the Oakland A’s and the New England Patriots have famously used business intelligence to find great success. Using data and analytical models, the Patriots won the Super Bowl three times in four years.
Restaurants like Wendy’s and Ruby Tuesdays use analytics to figure out which stores are succeeding, and which menu items to add or remove. Retailers such as Wal-Mart and Amazon use analytics to determine what business policies work and which ones do not. Indeed, it seems that business intelligence and data analysis represent the future of business decision making more generally.
Business Intelligence Governance
Business intelligence (BI) governance sets the rules by which business intelligence operates within an organization. Good BI is essential for organizing, steering, implementing, and developing BI strategies that are in line with the strategies of the company as a whole. BI governance will coordinate these efforts among different stakeholders with disparate interests. A good BI governance policy is made up of a number of components –
BI Governance Committee
A BI governance committee should be implemented to bring together different departments and interests to coordinate efforts and reconcile differences. It should be composed of a variety of people from different departments. It should involve all levels of your company, from end users to senior management. It should accurately reflect the diversity and different interests that exist in the company.
Some subject matter experts from IT should be included as-needed. Each member of the committee should bring the interests and perspectives of their department to the table. Comparing these priorities will clarify which projects are worthwhile, and reduce redundancies and missed opportunities.
In particular, this committee should help to bring together decision making processes to include the disparate focuses of business units versus IT. Business units will focus on aligning corporate strategy with BI applications and usage, whereas IT will focus on infrastructure and architecture decisions. The governance committee will be the primary decision making body to reconcile these different priorities. Therefore, the committee must have the authority to enforce its own decisions.
BI Lifecycle
A BI lifecycle is an infrastructure developed to support BI needs. This framework should be appropriate for any project regardless of the size and the scope. These aspects can be used separately or together depending on the nature of the project. The framework includes six sections –
Tool Selection – Select a BI tool that is right for the job. This will depend on how many users require support and their types, data presentation needs, etc. When possible, find a tool within your existing tool suite in order to save time and money.
Data Integration – Data Integration consists of making sure the data is relevant, available, and complete. Assess the condition of the data – is it high quality, available at the right frequency, and complete? If the data is in a form inaccessible to your BI tool, a data acquisition project may be necessary to access the data.
Analytics – This step involves ensuring data presentation and ease of access, making sure the data is presented in a workable format. These three steps are at the heart of BI lifecycle.
Custom BI Tool Work – Ensure the BI tool provides the right functionality for end users. Depending on the skill levels and needs of end users, different degrees of customization may be necessary. This fine tunes the processes to suit the needs of end users.
User Acceptance – Make sure the end users are able to engage with each step of the process. Ensure that the needs of the end-users are met, and that everything is working properly.
Training – With each individual’s expertise in mind, tailor the training to the audience. This step will ensure that end users are able to utilize the BI tool.
End-User Support Structure
This involves providing help desk support for end users. Proper support will include education on how to make use of the new data, on the functionality of the tool itself, and about business goals. This will keep the use of the BI tool coordinated with business goals. It will keep IT partners and end-users on the same page. Continuing to receive end-user feedback through this support structure is essential to continually improve the BI process. Through this process, the end-users themselves will push the evolution of your BI strategy, while working out the kinks in the established process.
BI Program Review
This ensures the functionality and value of your BI program. In taking a step back, and measuring success, you can quickly and easily see what is working and what is not. What has your Bi program enabled? Better business understanding? Clarified direction? Optimized relationships? Or something else altogether. Answering this question will help define the metrics by which to measure the success of your BI program.
In the case of Data Mining, questions like below discussed in the support structure component, end-users become the best resource for program review, as their feedback can cover a wide range of the facets of a BI program.
- Is it helping to reduce costs?
- Will it help to increase growth?
- Will it Increase your customer base?
- Has the BI governance committee helped to increase the speed of decision-making?
- Are capabilities realized well?
- Are IT partners and business units operating on the same page?
Final Words
Business intelligence has become essential to the workings of so many large, modern companies. If used properly, it can be of great benefit to your company. But without a BI governance framework, problems quickly arise and the potential of the data to increase value quickly drops.
BI governance helps avoid conflicts between business functions and IT and improves the working relationship between these interests. This will ensure that the data is of high quality when it arrives, and that it is taken full advantage of on the business end.
A reliable BI governance program ensures the quality of data and takes into account the perspectives of various departments and end users. It ensures end users have the training and tools necessary to take full advantage of this data. Without BI governance, business intelligence is far less valuable to your company.
