5-steps
Statistical Data Analysis

The 5-Step Plan for a Successful Business Intelligence Program

More and more organisations see the benefits in using quality data to drive their businesses forward, and for good reason. A recent study by the Economist Intelligence Unit - dubbed The Data Directive - that draws on a survey of over 300 businesses, has found that there is a correlation between the superior use of data with a positive impact on overall earnings and business performance. What it boils down to is that organisations that successfully leverage their data for strategic advantage are performing better than those that do not.

Embracing the use of business intelligence technology will help organisations achieve success through data exploitation if done correctly. Organisations that don’t develop plans for using quality data to their advantage will find themselves left behind. Here are some tips on how to get started:   

  1. Define the vision: Evolution of BI technologies provides an in-depth understanding of what can be done with the data. New advances in BI have the potential to support business objectives. New types of BI visualization technologies can support the exploration of data-sets in a much more amorphous manner, and aid in the discovery of patterns, segments, unobvious relationships and outliers. The fundamental problem is to figure out what questions to ask and work out which data matters the most. Leveraging BI, organizations can get a 720 degree view of the customer’s requirements. Hence, an insight into the big picture is required - one that receives support across all organisational functions and establishes how the organisation can successfully evolve with a clear vision.
  1. Define the business outcomes: A vision and good intentions are only the starting point for the successful use of data. In order to avoid the programme falling by the wayside after the initial euphoria, it is important to set specific and measurable targets for BI projects. One needs to leverage a mix of top-down and bottom-up approaches to identify potential business use cases. A top down approach can be used to identify KPIs (Key Performance Indicators) and bottom up approach can be used to determine the data to improve the KPIs. It is recommended to look for quick wins – use cases which can be improved in a short span of time to ensure continued business support. 
  2. Build the organisation: Insights from the EU Data Directive research have shown that beyond data-specific concerns, a lack of skills is one of the key barriers in building a successful data-centric organisation. There aren’t a sufficient number of people in organizations as well as the marketplace with the right set of skills to make the most optimal use of data. One of the strategies adopted by the organizations leading the data revolution is to appoint a chief insight officer or a chief data officer, for industrialization of actionable insights.
  3. Consider governance: organisations that prove they are committed to the balance between privacy and value will win the support of their stakeholders. If you are considering implementing a business intelligence solution to move to a data-centric organisational model, creating a Centre of Excellence or BI Competency Centre comprised of people who understand both – the company’s business and the IT environment – may be a very good idea. The team will be able to help build a BI system that is flexible and adaptable, a very important factor if the programme is to stay relevant as the business evolves. The centre will also be able to ensure corporate governance principles are met, can help monitor user adoption and benefits realisation, and drive enterprise-wide standardisation of the BI system.
  4. Test the technology: Entire BI and data architectures need to be evolved to handle real time fast moving data at optimal cost levels. Begin by using tools with which the organisation is already familiar and move ahead with pilot studies. Many organisations may already have experimented with business intelligence technology in the past with varying success. You might have encountered problem areas such as low adoption rates, scepticism among users, issues with the technology and a lack of executive support. The resulting intelligence reports may also have been lacking in common data definitions and have only limited usefulness for the decision-making process, failing in the exact area where you were hoping the technology would help. The problem is that very often, BI programmes are unsuccessful because it is seen from either a business or a technology perspective, when in reality both aspects are just as important. However, by having gone through the motions described above, you will have already eradicated the potential problems you may have experienced in the past.  

Data analytics is a big trend in the business world today and for good reason. However, as with everything in business, there is no one-size-fits approach. Every business is different, with unique needs. However, by looking at what you want to achieve in the business and working backwards, instead of buying-in a system and then adapting your organisational culture to it accordingly, you are likely to uncover new and better ways for growing your business with the help of your business intelligence system.

 

K R Sanjiv is Senior Vice President and Global Head, Analytics and Information Management Services at Wipro

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K R Sanjiv

K R Sanjiv is Senior Vice President and Global Head, Analytics and Information Management Services at Wipro

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