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The key to being Data-Driven is Being More Human

When we are called in to digitally transform a business into a data-driven organisation, we start by working to understand the drivers of trust and community building within that organisation.

This approach is founded on a philosophy that the fundamental challenge for a business going forward is to build sufficiently sustainable human systems using the technology that we have at hand.

If you consider the explosion of data that digitisation has caused through the aperture of the speed of which that data is now being transmitted, it has accelerated so rapidly that this data explosion has effectively overwhelmed the filters that enable our society to derive authority, trust & belief – filters that were long ago created by human systems.

It seems that, post the ‘Information Age’, we have created a situation where there are a whole lot of people who don’t understand how the digital systems work and operate, and we find the trust has been eroded in many of the areas where technology should actually work to create outcomes.

To win back the trust of the people we empower through technology, technology providers need to seriously consider: how do we treat data with dignity?

To start with, we need to ensure that there’s equity in the participation of how that data might be used or enriched so that people understand the choices that they’re making when they participate. There shouldn’t just be a case of a one-sided view of that data and its application.

In the creation of tools for our own people and our clients’ people, we come to it from a more humanist angle – we believe that there are a number of clear issues that are beginning to surface in the way humans exchange data, the usage of that data, and the value systems that are being affected by that data.

There’s a lot of static in the air, and that comes from the fact that, to effectively talk about becoming a data-driven organisation, it means first becoming a digital organisation.

One of the things organisations have got to do is have the courage to change, and part of that change is having the courage to sweat the little things.

When you are in possession of data, it means that you will discover 10 things you can do something about. Being a data-driven organisation means, you actually have to look at all of those 10 things.

The only way to do that effectively is to very rapidly broaden and open up the aperture of information processing through the organisation – which happens to be your people.

In the technology industry, management systems have had to change from the traditional hierarchical drop-down model to a more collaboration-driven, agile, rapidly “twisting time” model. The challenge with doing that properly is that you don’t have time to send it upstairs so someone else can make a decision – every person has to have both the courage and the accountability to ‘get on with it’.

There therefore has to be a strong sense of trust in that environment and trust in the data flow.

And this is why most organisations pause right there. Overcoming the next challenge means having the courage to diversify your data set and information flow. Adopting the markers of that change requires rewiring the entire business and empowering other voices. So they choose to focus on iterating process instead of people.

The problem for us as human-focused digital transformation consultants is that this outcome of organisations choosing to fixate on digitising process rather than empowering people, comes from our own frustrations.

The fundamental point of departure is (and Arthur C Clarke put it best): “Any sufficiently advanced technology is indistinguishable from magic”!

Now here I come as a data scientist or a technologist or a data-driven individual to tell an organisation, “The data says that if you want to be an effective team, you’ve got to start by throwing away these prejudices you currently have in your organisation about who you think is effective and at what.”

And “Now you better believe me and you better trust me because that is the only thing you have to go on because the rest of it you will only understand after this pivotal shift in mindset” – it’s indistinguishable from magic.

For us, the pattern is obvious.

And that’s our challenge as a technology industry. Because we have not yet created an equitable, transparent, participatory culture around what we do with people’s data, we haven’t exactly covered ourselves in glory, when it comes to trust.

How do we go about building that trust?

We’ve got to put some new topics on the table – the things that have not been talked about, that need to be talked about.

That’s only going to come, if we truly want to be inclusive, from an emerging market perspective; from teams that are currently dealing with these realities.

Part of that is the willingness to listen when those far corners of the “data pool” speak up on the unintended consequences that an uninformed technology practice can lead to.

For example, Facebook has a habit of testing algorithms in, I guess what they would call ’emerging markets’. Sounds harmless, an approach to testing within a data set.

To me this sounds a lot like: “Hey, let’s experiment in this third-world country, before taking this new feature larger.”

I personally think the data set in downtown Palo Alto is more diverse and denser than the entire country of Namibia. The thing is they don’t choose to run this test of their algorithm in downtown Paulo Alto – they run it in the entire country of Namibia.

And the question we’ve got to ask ourselves becomes: “So… if this algorithm causes some kind of damage or lack of trust in communities because fake news starts getting injected, etc. etc. … Then what?!”

As it turns out was the case.

But what about this human collateral damage we’re leaving behind?

And who said we can do that anyway, actually?

And that comes down to when we are modelling this data and when we are gathering this data, are we looking at this as people, as humans, first?


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