BI - Common mistakes to avoid for Enterprise Business Intelligence and Analytics projects.





  • Be wary of choosing platform based on hype. Select the tool based on your business needs, alignment to strategic and architectural direction, operational goals and constraints and  competency of your staff and customers.
 
  • Leapfrog, but not too far– in certain cases, being re-actice instead of proactive will be the right choice. Model the expected outcome using spreadsheets and POC before signing big check.

  • Do not overlook the user experience. It has to look appealing at the glass (browser). Many implementation team focus on data processing, but do not pay attention to the UI. This inhibits user adoption, and maximizing value out of the tool. Hire experts with visualizations skills if you do not have resident staff trained.'

  • Pre-built solutions will need configuration, irrespective of what the salesperson may say. Plan adequate time to close the gaps in the out of box tool and stabilization. Try releasing to a pilot user base. Make sure there is a cultural willingness to embrace the best practices and industry metrics before buying the tool. Budget for change management, governance, training and feedback gathering          
  • Set up goals that matter to the business (Revenue Growth, Cost Management, Customer Satisfaction, Product Quality). Do not focus on only the reporting automation aspects. Think how it will provide metrics to achieve corporate goals. 
  • Don’t fall for the buzz words such predictive analysis, statistical engine. Understand the statistical model, test it with your data to make sure it gives meaningful results. Ensure adequate data volume for statistics to be relevant. Avoid ending up with unpredictable results leaving you and your users scratching their head. 
  • Do not get swayed by sales pitch. Teams often confuse the UI with the data value. UI and usability are important, but will give meaningless results if the process is not mature. The bigger challenge is capturing right process data consistently with adequate checks and balances to achieve goals of analytics

  •  BI is not a one-time event – it is a journey. Start the journey with a solid business case and ROI.

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