Analytics – the new path to value: IBM/MIT Sloan study

IBM and MIT/Sloan recently published “Analytics – the new path to value“. This study had a lot of interesting points and was very decision management centric in my mind. Some thoughts:

• The main challenges for companies adopting analytics were innovating to be deliver competitive differentiation and growing revenue.
  Reducing costs, gaining efficiencies and profitably retaining and acquiring customers were the next three. This focus on top-line value is interesting and reflects a growing interest in what I call opportunity analytics.
• Interestingly, organizations that are more sophisticated with analytics are 3x more likely to be in the top 17% of respondents by business performances.
• Similarly those top performers are 5.4x more likely to use analytics rather than intuition.
• The key obstacles to analytics were a lack of understanding how to use analytics and lack of management bandwidth due to competing priorities.
  Lacks of skills, ability to get the data and sharing/ownership of data came next.
• The study assessed different techniques assessed for value today and in future. Today standardized reporting and historic trend analysis/forecasting were top but both trend down sharply – to 5^th and 7^th. Meanwhile visualization, simulation and analytics within business processes rise to the top 3 (from 3^rd, 5^th and 4^th today). More formal mathematical techniques also moved from 7^th to 4^th. These techniques help turn insights into action and are clearly perceived as growing in value.
• IBM/MIT identified three segments
  • Aspirational (33%) and focused on analytics to reduce costs
  • Experienced (46%) still focused on cost but revenue too and working on sharing information and insight
  • Transformed (21%) more analytically sophisticated, targeted revenue growth and feel the most pressure to do more
    I think this pressure is higher for analytically sophisticated companies partly as the see the value and its potential but also because they are in analytic industries and have more analytic competitor
• IBM has a five point path to success:
  1. Focus on biggest and highest value opportunities
     I would urge you to remember that operational decisions have a big multiplier so don’t go for biggest single decision but the biggest total value (# of decisions  x value of decision)
  2. Start with questions not data
     I have been saying this for years – begin with the decision in mind
  3. Embed insights to drive actions and deliver value
     Well adopt Decision Management!
  4. Keep existing capabilities while adding new ones
     More sophisticated companies use LOB and central analytic resources more relative to IT/point of need resources.
  5. Have an overall information agenda
     Worry about big data, governance, data management, analytic tools (don’t forget to industrialize your analytic process)
• IBM uses Process Application Data Insight Embed process (PADIE) to capture existing applications and processes, identify insight and data that can solve pain/add value and then embed the insight into the operations. This sounds a lot like my approach – Discover Decisions (in your processes), Build Decision Services (to apply analytics to these processes), do Decision Analysis (to ensure continuous improvement)
• To drive success they recommend that aspirational companies focus on big issues and begin adding specialists to build on existing capabilities while building an information agenda. Experienced ones should build a strong central team and keep their information agenda  up to date to move to transformed.
• Getting started advice:
  • Pick your spot
    Your decision
  • Prove the value
  • Focus on continuous value delivery
    I would add for both the decision and across the organization

Great results. You can download the whole study here