It's an extraordinary period of time. A computer that is sitting on a UK knowledge workers desk today is probably equivalent to a supercomputer 15 years ago. But not only do they have this incredible computing power, they also have access to more data than ever before.
Then, they have this second element – algorithms. Software is enabling you to do things that you really couldn't have easily done before. Things like vision and image recognition, natural language processing or the ability to create incredibly accurate forecasts using advanced machine learning algorithms, for example.
When companies combine those elements, they are in an incredible position to harness their power and deliver breakthroughs to their business models, as well as to the efficiency of their operations.
This has really been the making of a couple of decades of transitions. But the convergence of data, technology and culture has really put companies in an incredible place to transform themselves.
One of the things that we've seen at Alteryx is that it's not in one specific area that these transformations are happening.
We see it in marketing and sales and logistics and kind of these bigger use cases that, that I'm sure you've read about. But we also see it in the tax office and the HR department and the legal department.
So, one of the challenges for a CDAO is transformation. ‘How do you get it to happen across all of the areas of the business, beyond purely digital, to educate and steer the entire business to be data-driven?’ That is really what the leaders in this space have figured out.
At companies like [specialist accountant] Brookson, we have seen incredible transformation happen as they take customer data and analyze it, leveraging Alteryx to provide customized tax advice at a new level of scale that just wouldn’t be possible with their prior processes.
Similarly, one of the world’s oldest and most complex nuclear decommissioning plants, Sellafield, had a dire need for advanced analytics. Using Alteryx, they’ve started predicting the contents of nuclear waste containers using neural nets, doing sentiment analysis with safety event logs to improve safety and helping the government use spatial mapping to visualize all nuclear decommissioning work in the UK over the next 40 years.
The diversity of solutions is staggering and the impact on businesses, and society are equally awe inspiring.
When I meet with companies, this is frequently a question I get asked. But obviously, there are so many use cases in so many places. What the right ones will be depends where your company is on the journey and what data you have available.
So, what I try to bring it back to is harnessing your workforce. The best way for a CDAO to generate high ROI will be to get the right tools in the hands of their employees and enabling them to go get that ROI.
It's typically not the case that I’ll see a CDO pick just one single use case, hire a data scientist, implement that one use case and transform their business. It's more a matter of enabling hundreds of people and creating a culture of analytics, allowing them to change processes, transform how organizations interact with their data and change the way that the business is being done.
Everybody talks about this 'digital transformation' and I think most people get very enamored with the word ‘digital’. But it turns out that's the easy part. It's the second word that people are struggling with: Transformation.
That’s why most CDAOs are actually typically not coming from technology backgrounds. They're change agents because transformation is hard. It's hard for individuals to transform themselves. It's hard for departments within a company to transform, and yet even harder if you want to transform an entire company. That, I believe, is the big challenge.
It's unfortunately not as easy as, ‘Well, you just do these three things and, voila, you now have transformation.’ But there certainly are best practices that we see out there. We see people putting in strong analytic governance, for example.
Governance, to me, is not a bunch of rules to follow. Think of governments. What is a ‘good government’? It's one that provides a framework within which their citizens can succeed and thrive.
Good governance is an enabler for achieving corporate objectives using efficient and effective best practices that enable the workforce.
So, have you set up analytic governance processes people can use to get help with the tools and guidance they need to solve the problems they have? Have you set up design review meetings to share best practices? Have you put in these basic things that are required to bring people on that journey?
As I say, it's a special time in history. The convergence of computational power, data availability and software capability is unprecedented. Entire businesses are both being born and revolutionized by people who know how to leverage these capabilities.
As analytical processes become as much a part of the average business user’s palette as email, CRM or their HR software, you've got to ask yourself, ‘Is your company going to be a leader in this revolution? Or are you going to go the way of Blockbusters and Sears and the many other companies who've basically been displaced because they weren't able to transform fast enough?’
It's an incredible place to be as a data science or analytics professional. Fundamentally, the ability to help a business leverage their digital assets to solve business problems and transform is going to determine its success or failure.