Creating an in-house Best-in-class training unit for Analytics

I like the phrase EBM – Evidence Based Management. In the last few decades, there have been great efforts to capture and store data of all kinds. The natural next step is being able to explore the data, see patterns and then, take decisions on the basis of this ‘non-predictive analysis’. As the data, reporting and non-predictive analysis stabilizes, we naturally become more confident and aim to predict outcomes through ‘predictive analysis’.

In my view, Analytics is a skill, an amalgamation of

  1. Understanding the domain / business
  2. Understanding scientific / statistical methods
  3. Using a software to implement the statistical method
  4. Drawing insights / conclusions which help make better business decisions.


The above mentioned process has evolved from Supply Chain management and Just in Time Concepts, Six Sigma, and Business Intelligence and now, has a much larger reach / depth and is called Analytics.

Analytics is a growing domain with newer types of data, softwares and statistical processes adding into it, on a continuous and regular basis. The speed of growth that Analytics is undergoing today is exponential. Thus, the thought process for setting up an ‘always relevant’ training practice to support a delivery team which has to constantly be updated in skill sets ,  is a challenge which sets it apart from an established management function (which grows at a steady rate) .

Any Corporate training cell seeks to Create, Maintain and Deliver trainings for:-

  1. New Hires to
    1. Familiarize them with business concepts most used in the company / function
    2.  Understand and work on Delivery methods used within the company / function
    3. Inculcate Corporate philosophy.
    4. Existing employees to
      1. Introduce new / advanced concepts for the employee – which is often an established concept for the company / function
      2. Update knowledge w.r.t new concepts.

A large part of the Creation, Maintenance and Delivery does not require frequent changes. At the same time, as already discussed above, Analytics is a domain which is increasing in scope at a breath-taking rate.

What a training cell for Analytics should aim to do:

  1. Create a process of dynamic learning – a process by which newer analytics projects can be understood and refined by the trainer , with the business, to
    1. Create new content
    2. Update existing content
    3. Update trainer’s knowledge
    4. Understand the skills (technical, soft skills, business knowledge, client management etc.) which drive client satisfaction for the Delivery team .


Here the linkage between the delivery team and the training team demands the   synergy that is seen between the driver and the navigator in a rally car.  The thrust is how to bring the newest concepts to a larger public in the least possible time.

  1. Create a team of Trainers who have an understanding of and pride of being part of the organisation’s growth in dollar terms.
  2. Create a Process of measurement of efficiency and contribution to business success.
  3.  Create a process of High involvement of the training team in career pathing exercises and as an advisory / counselling team for the unit in terms of career planning and growth.
  4. Increase intellectual property for the Management education system by transferring information and content to Centers of education. This may tie up with the Corporate social responsibility initiatives or can be monetized- depending on the larger organisation goal / philosophy.
  5. Create linkages with the HR sourcing process to
    1. Improve the rate of acquisition and quality of new manpower
    2. Reduce attrition rates
    3. Improve employee satisfaction scores.

If we have the luxury of starting a training team for a practise which has been in existence for some time and has a certain maturity, a good point to start would be to

  1. Assess and document the Urgent vs Important requirements for training as perceived by the Analytics Delivery units
  2. Understand the challenges in recruitment and skill development as perceived by the HR and Senior core team in Analytics for the near and medium term (next 3- 6 months)
  3. Understand the longer term vision for the Analytics practise (e.g.  new areas that are seen as potential areas of growth, numbers for 3 – 5 year horizon )

With this understanding it will be relatively easier to create a team and process for effective Content Creation and Management and Delivery of training and workshops.  A core philosophy of Analytics process (e.g. DCOVA) should become the backbone and guiding thought which will bind the unit together – through Delivery and Training, ensuring a common way of approach and solutioning to Analytics projects.

A number based Analytics plan can be created once consensus on the overall deliverable is agreed upon and parameters / metrics of success are frozen.




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