Digital Transformation: it's easy to prioritise technology and data first.

2022-10-10 |  A Kuppan

With the Reuters #pharma2022 event coming up, one of the themes is “Comprehensive frameworks for equitable access and accelerated digital transformation… but progress is slowing risking a return to the old models”. This left me reflecting.

With so many of us focusing on more digital opportunities, the topic of having so much data but still struggling to understand what to do with it is still coming up.

This is the reality we find ourselves in.

In fact, with increased volumes of data, it’s seemingly become even more challenging to measure and correlate to impact. I can’t help but question if digital has indeed made it harder or is it because we are so focussed on the enablement of channels and content ahead of anything else.

In my experience, traditionally there has been more focus on technology, big data capabilities and integrating platforms. Whilst these are valuable enablers and have enabled so much in the past, it is easy to underestimate the value of the other facets of planning e.g.:

1. Protecting the time to think and map out a plan to utilise all of your resources

  • Prioritise what you are trying to solve for or hypothesis to test and how will you know if you’ve succeeded (success factors)
  • Find the right types of data and plan for how you can integrate it, don’t ignore external and open-source data and document it for compliance and retaining contextual knowledge
  • Leverage (or source) the right skill capabilities to resource advanced analytics functions.

2. Documenting success factors and how they can be measured

I’ve seen many occasions where because there is a wealth of internally generated data, the goal is to mine it hoping to find the nuggets. Instead, define a hypothesis to test and a set of criteria to track its progress towards your goal.

A colleague of mine once said, “If you don’t know where you’re going, any road will get you there.”

  • Test and learn; use the learnings for the next hypothesis or priority. Easier said than done so help your teams by defining and socialising a process to enable this holistic and agile approach.
  • Also, consider what you could measure or track that could quantify the changes as a result of the learning and action. Your leaders will always need to know if you are shifting the needle.

3. Securing commitment to the vision and building trust in the foundational data quality.

This is an area that can be underestimated in favour of enabling more channel capabilities. That line on the project plan for “roles and responsibilities” not only for data governance and stewardship but also for sustaining and naturing organisational capability is easy not to satisfy and needs discussion time upfront.

  • Show the “why” and support them to understand the “how” it can impact them in their reality and from their frame of reference through use cases
  • Roles and responsibilities especially for data strategy including ownership, governance and stewardship are critical for operations and perceptions to build trust
  • Look for opportunities to share smart failures to build institutional knowledge and nurture the behaviours you need through communities of learning
  • Allow the teams to own and foster sharing and empowering recognition.


It’s easy to make digital transformation all about turning on another channel, enabling more content and features, launching more opportunities, and searching for benchmarks. Transformation should be about leading innovation and fostering the behaviours you want to see. The challenge is protecting the time to focus, plan and lead by example.

Are you going to #Pharma2022 in Nice from 11-13 October 2022, it would be great to hear your thoughts and ideas over a coffee. Please let me know in the comments if you will be there and, even if not I would love to hear your ideas and or experiences on this topic. Is progress slowing and risking a return to the old models?