No more Lipstick on the Pig !!

What does data, scale and automation have in common?

To answer, we have some unpacking to do. Some obvious, some not so obvious. Let's start with the obvious.

Our world is becoming increasingly digital. At work. At home. While we exercise. While we sleep. Digital is infiltrating all aspects of life.

But what is digital? It may sound like a silly question, but with so much noise and fluff, it is hard to see the forest for the trees.

Remove the unncessesary so that only the necessary remains

When removing the noise, fluff and everything unnecessary from digital, only two things remain; the fundamental building blocks: 0's and 1's. And 0's and 1's are.... DATA. Everything digital is data.

Think of data as lubrication, and data quality as the amount of lubrication. The higher the data quality, the more we lubricate. Some might say that fuel is a better analogy, but I think lubrication is more catchy, as it directly relates to the challenges of scale and automation.

The "F" word is the digital world is Friction"

The "F" word in Digital is Friction

Lack of lubrication creates friction. Everything in our physical and analogue world creates friction. A typical car typically converts on 20% into velocity, the rest is friction. Unless it is an electric car of course. Even sending electricity down a wire creates friction, in the form of heat. Every energy exchange creates friction. It is as unavoidable as death and taxes.

Here is the kicker: When we remove friction we get scale! Especially in the digital world! Indeed, this is the only reason we do digital.

But what is scale? It's a bit like being a teenager. Everyone talks about it, but few do it. But not from lack of trying!

Let's first define scale. Scale is growth at near-zero cost and breaks the traditional relationship between cost and revenue. Put simply; it allows an organisation to grow and create value without adding employees or assets. Think Uber, which creates value using non-owned assets (people's cars).

Most organisations are trying, through initiatives labelled digital transformation. According to IDC, global spend on digital transformation will exceed USD6.8 trillion between 2020-2023. This equates to a third of the entire US economy!

With all that money, surely we must create a lot of scale? Not according to the experts. McKinsey research indicates that only 16% of digital transformation projects deliver sustainable value (up from 27% in 2015).

McKinsey research on digital transformation

What is going on?

Let's get to the heart of the matter.

Any system not designed for scale….  will never achieve scale. No matter what we do!

A strong and opinionated statement, but why keep putting lipstick on a pig? Why keep trying to unravel things that were designed for a non-digital world? For example, if we design and build a CRM, or ERP or any system, with the mindset of the past, it will fail.

The keyword here is mindset. Scale does not originate in doing something different; it originates from thinking different. A mindset where data takes the centre stage. This makes sense as everything in the digital world is data.

The complication is a mindset rooted in process, encapsulated in the well-known analogue framework: People, Process, Technology. This framework is originated in the mid 1960s, which makes it more than 50 years old. What else in organisations do we use that is 50 years old? Not much!

Its focus is internal, and on minimising friction through productivity and efficiency. But in today's world, with emerging ecosystems, an external focus is needed. Coming back to the Uber example; Uber creates value by leveraging an external ecosystem of physical assets.

So what do we do?

We replace process with data, and create a digital framework: people, data, technology. It looks simple, yet the mindset change needed is.... enormous! We are not just talking about putting data in the centre of decisions. Bad data simply leads to bad decisions. We need to put data in the centre of designing systems and operating models.

In the process, we need to let go of much of what we have learned in the past. This has been relatively easy for pure digital players and digital disruptors, but what about traditional organisations? How do you deal with existing data, processes, mindsets and culture?

This will be described in my next article, where I will unpack a digital transformation case study, in a traditional organisation, that improved a core process by almost 300% (or a multiplier of 2.9X to use digital lingo). Salesforce was the business platform used, but the approach can be used on any modern data-driven platform.

You can also watch the video version of this post that has more stats and graphics:

Until then, please comment, like, or share your experiences. What mindset challenges have you come up against? How did you solve them?

JL

Jesper Lowgren is a published author, speaker and data architect and thought leader. He specialises in helping traditional organisations create scale and automation through data-driven design and transformation.

Jesper is Swedish and apologises for any Swenglish creeping into his writing. He is the published author of two books on business and personal transformation, available on Amazon.