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9 Ways to Improve BI in the Organization

1 September 2011
Shlomit Amichi
A person holding a tablet with charts

The best way to justify investing in a BI system is to choose inefficient processes where data mining through a BI system will quickly contribute to making better business decisions and demonstrate how the company can improve plans, shorten timelines, generate profits, and show efficiency.

During economic revolutions, BI initiatives stand out for their potential to improve organizational performance through better data collection from various systems. Compared to many technology projects, BI requires relatively few resources. One of the critical trends today in information technology is the emergence of BI tools that aim to address various business issues.

The investment in BI is worthwhile for most organizations interested in adequately implementing it. They take the time to fight the political and technological battles required to ensure that the data they analyze is complete, they root out errors to ensure that the analysis the tools produce is reliable, and, most importantly, they create customized data views for key users/customers so that senior management and finance people have immediate access to information that will allow them to perform better and better deal with opportunities and threats.

It is essential to understand that BI is not just technology but mainly management.

According to Gleansight's comparative report, there are nine ways companies can maximize the value of their BI investment.

  1. Tailor the data display to the needs of different roles. The CEO, HR manager, and call center manager must receive other information tailored to their area of responsibility's key performance indicators (KPIs). It is crucial to adapt BI applications to the different needs of users in the organization and identify a data display that will give each of them the most excellent value for performing their work.

  2. Integrate data from different departments and systems. Especially in large organizations, multiple BI tools are used by other departments. Attempts to integrate these different applications can sometimes be frustrating, as when the organization acquires another company that has already adopted a different BI tool. In such a case, complete homogeneity should not be expected. Nevertheless, the more data retrieval from multiple systems can flow into a single data warehouse, the easier it is to generate cross-functional and cross-departmental analysis. The more users can get the information they need from a single dashboard or portal, the shorter the time for productive use of the BI tools.

  3. Encourage a culture of data-driven decision-making. Management support is critical to success, as is any system-wide implementation in the organization. There is nothing like the company's management saying, "This is how we do business from today," to encourage system use. When management aims to manage through KPIs displayed by the BI tool, anyone who wants to gain trust will make sure to use this tool as well. Praise decisions based on precise data, reject decisions not based on this data, or made without examining them. Recognize that sometimes decisions must be made even without data or with ambiguous or unreliable information, but clarify that using data for decision-making is an organizational goal.

  4. Implement a process for continuous data quality improvement. Data quality will never be perfect, but it can constantly be improved. Errors "creep" into manually managed data, and distortions can occur when merging data from multiple systems. Create a systematic process to identify and monitor mistakes and distortions. For example, data validation at the data entry stage should be improved, data should be double-checked, and data cleansing software should be implemented that identifies data inconsistencies and deviations.

  5. Present a plan to improve operations and outputs. In the initial stage, the best way to justify the investment and improvement in the BI system is to demonstrate improved business results. Look for inefficient processes that will quickly benefit from data-driven decision-making. Show how the organization can improve planning, shorten timelines and budgets, and increase efficiency and profits.

  6. Implement an official KPI methodology, such as a balanced scorecard, Six Sigma, etc. Ultimately, what matters differs from how many reports or graphs you created and what you did with the information you received. To get better results, learn from the experience of others who have already researched and studied the subject.

  7. Deploy alerts. Giving managers access to data retrieval is not enough, especially if they must respond quickly to threats or opportunities. They should be able to receive an alert when they are on the verge of an opportunity or when such a threat arises. Such an alert can be integrated into an existing alert system in the organization or reflected in the data displays. Additionally, it is recommended that each user define such alerts for themselves.

  8. Train users. Although BI tools are often promised to be easy, some employees will need training. Budget for this within the project and, depending on the type of users, determine whether it is appropriate to conduct one-on-one training, prepare training materials and self-study aids, or conduct multi-user training.

  9. Improve analytical capabilities. Creating sophisticated analytical tools and nurturing analytical skills are essential to adding value to BI investments. Through the application of data mining and forecasting, uncover unexpected, hidden, or non-intuitive patterns. Nurture a team of analysts with appropriate knowledge and experience to improve data interpretation capabilities.

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