New MOOC on EdX: Platform Business Models

A new MOOC launched online on EdX today.

Today (18.6.21), we also launched a new MOOC (asynchronous online), instructor-led course on Platform Business Models:

If you are interested in platform business models, consider enrolling in the course today.


Srinivasan R

New Book: Platform Business Models: Frameworks, Concepts and Design

Writing after a long time …

Have been busy completing a book. Launched today in an online event.

Book is now available online:

Print version will be available soon.


Srinivasan R

Digital transformation imperatives

I wrote a blog post on digital transformation stages about two years ago (yes, it has been two years!). In that post, I outlined digital transformation as a process and outlined a four-stage model. Over the past couple of months, I have been leading the IIMB executive education programme on Leading Digital Transformation. This programme, offered jointly with the Friedrich Alexander University of Erlangen-Nuremberg and the Fraunhofer Institute of Integrated Circuits IIS, has attracted an impressive class of participants (2018 being the pioneering batch)*. I have been closely interacting with the participants of the programme, who are leading/ looking to lead digital transformations in their respective enterprises over their modules in Bangalore and Nuremberg. As I sat through their project proposal presentations, three thoughts flashed through my mind:

  1. True digital transformaton is possible only when there is a mindset change.
  2. Process reengineering should help the enterprise seek to add new/ additional value, rather than just more of the same value.
  3. Enterprises should proactively plan to utilize and leverage the large amounts of data such transformational journeys generate, failing which the value added wouldn’t be sustainable.

Digital transformation as a mindset change

Digital transformation is not just automating processes, or introducing fancy technologies in the workplace. There are a lot of organizations out there that have embarked on the slippery path of digital transformation without fully understanding what it takes. I remember the early days of computerization where just introducing computers was not sufficient – it was important to highlight how and why computers helped improve organizational efficiency (reliability of repeatable processes). Managers resisting change would bring out instances like, but organizational decision making cannot be programmed, and therefore technology change is likely to result in loss of employment and subsequently, control. I hear the same arguments today … especially with respect to automation and artificial intelligence … the human touch will be gone, digital assistants cannot replace human beings, and the like. It is imperative for leaders to communicate at both the far and near mindsets (read more about far and near mindsets here) to effect acceptance and adoption.

New/ additional value creation

Leaders should consistently communicate the new value created as a result of digitalization. Just additional value (more of the same) does not always justify the investments in digital transformation … even though the competitive context may demand so. For you to do more of the same things, add the same value, you just need to digitalize your existing processes, and make them more efficient. For you to add new value is when you need to embark on the process of digital transformation. And this happens when you begin looking at processes with an intent to re-engineering – have a critical evaluation of the processes and drive change at the process design layer, rather than at the execution layer; and ensure that new/ additional value is created and appropriated.

Descriptive, predictive, and prescriptive data analysis

Value creation/ generation is a function of process re-engineering and re-design; value appropriation is far more difficult. Effective value appropriation requires the organization to invest in deeper analysis of the vast amounts of data generated to be able to (a) describe (based on patterns in the past), (b) predict (extrapolate based on past data, as well as estimation of other parameters that affect the phenomena, and (c) prescribe a course of action (based on the juxtaposition of the description and prediction of the environment with the organization’s intent and capabilities). The criticality of descriptive, predicting and prescriptive data analysis needs to be articulated and socialized in the organization as a key to sustaining the digital transformation journey. In the absence of such insights, these transformational efforts will surely fade away, if not fail!

Such insights should provide the organization with the much needed data to convince its members on the short- and near- term value creation due to digital transformation efforts.


41.1 Digital Transformation imperatives

So, in summary, digital transformation requires an organization to continuously invest in mindset change, process redesign, and generate insights.


© 2018. R Srinivasan.

* Disclaimers: I am the IIMB Chair for Executive Education Programmes that markets these programmes; I am also the programme director (course designer and teacher) of the said programme: Leading Digital Transformation; and I am a visiting professor at the Friedrich Alexander University of Erlangen-Nuremberg. Apologies for the self-promotion, and the (unintended) marketing pitch for the programme.

About this blog

Hi: I have been wanting to write a blog for a long time. Thanks to my students and collaborators who have pushed me to write regularly, I start.

There are three things I would write about:

  1. Strategy, in general; Indian firms in specific
  2. Digital strategy, and what it means for the Indian firms, especially start-ups
  3. Platform business models, with a focus on Indian firms

Suggestions and comments welcome.

Reach me at


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