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The other day a friend asked me an interesting question.  Is digital transformation a function, a new business model or a software solution?

In trying to answer the question, I started listing some properties of “digital.”

 

Measuring:

The first thing about digital is “measuring”.

Digital allows us to move away from intuition and get into absolute numbers.  We know that going from 3 to 4 on a scale of 10 is much different than going from say, 0 to 6 on a scale of 10, even though both are “improvement.”

This gets us into the measuring mindset.

Over time, we have found ways to measure the abstract – as opposed to an intuitive feel.  Think warmth (temperature), spiciness (Scoville scale), color (colorimetry) and now even beauty is measurable (golden ratio).

This is measurement on a scale, with absolute numbers, which makes it precise and provides the digital element.

 

Data is coming at us in massive volumes:

The second property of digital is the sheer volume of data that is available today.  By some estimates, we humans generated more data in 2017 than in decades past.  With the growth in IoT and intelligent devices, there will be an explosive growth in data.  This is estimated to hit 44 Zb (Zetta bytes) by 2020 with no signs of slowing down.

1 Zb = 1,000,000,000,000,000,000,000 bytes!

One of the most impactful graphics shows the data generated in one internet minute – this is data generated mostly through human activity.

And very soon we will have an insanely massive number of sensors attached to every piece of article imaginable, sending out even more data.

 

Data is growing in real-time:

The third property is the speed at which the data is coming at us.

It is entirely possible to make a change to a web page, tweak the wording in a radio advertisement or send an email to a hundred thousand strong mailing list and find out very quickly the results of the action.

This speed, combined with the business value of analytics, is one of the main drivers for the new Chief Digital Officer role in B2C startups.  This position is one of the first hires primarily due to the impact on customer engagement.

 

We have excellent technology for accessing and analyzing massively large data sets:

The fourth property is the sophisticated analytics that today’s technology allows us to perform on massively huge amounts of data.

Technology allows us to process data to the tune of tens of billions of records.  It can handle various types of data such as text, numbers, images and even audio.  Technology is equally capable of handling unstructured data – there is no rigid requirement that data must be in a pre-defined form.

Improved algorithms can provide predictive and cognitive analytics on data, recognize patterns buried in complex data, quickly and with Machine Learning, can constantly improve the quality of results.

We also have a plethora of devices with which we can access and generate data.  We are constantly building sophisticated devices for this purpose such as smartphones, tablets, embedded devices, wearables and sensors.  This list of devices is growing and the capability of such devices is also improving.

 

Impact of all this Data:

The impact of all this data around us is causing companies to change their business models.

In an internet radio talk program re-imagining business models in life sciences,  Joe Miles states that, “massive amounts of data will be generated from patients’ smart devices, providing more accurate insights into patients’ conditions.”

As a result, for Life Science companies, their supply chains, manufacturing processes, delivery models and even interaction with physicians and patients will have to undergo radical changes.

In another related post, SAP’s Chief Innovation Officer, Marty Mrugal, cites an Oxford Economics study which found that only 3% of organizations are truly committed to digital transformation, while 78% feel that such transformation is critical.

If a large number of leaders feel that such transformation is critical, and a paltry few can truly commit to this initiative, then we know that this is no trivial task.

This transformation is a mindset change; a culture change in the workforce in companies including Life Sciences.

Such a sweeping change is neither easy nor can it be done quickly.  It will take strong leadership, strategic approach and relentless execution to transform the mindset of a critical mass of the workforce.  Then we can expect network effect to bring about holistic digital transformation in the enterprise.

 

In summary:

First, we have the data measurement part, i.e. coming up with the right measure.

This we can mostly leave to the scientists.

Then, we need to put in place tools and processes to collect, measure and report on the data.

This is mainly an investment decision.

Lastly, we need to bridge the gap between the data that is measured and the corresponding business results.  This calls for linking business results to numbers, identifying changes that will “move” the numbers and constantly improving. i.e. a culture, mindset change.

Digital transformation will yield real business results only when this final component is in place.  This is the most critical aspect of digital transformation and one that requires major change management.

 

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