In the 30 years I’ve been working in IT, I’ve seen so many tech booms and busts. Many technology phases and cycles. Business trends have come and gone. Despite all the noise, I’ve come to the conclusion that change agents – CIOs and CTOs – are wise to tune out all the babble and the buzzword bingo and focus on three things that transcend everything else:
- Revenue: what are we doing to improve revenue or margins?
- Customer experience: how are we giving our customers what they need, given the constant evolving nature of their journey and path to purchase?
- Employee experience: how are we ensuring that our colleagues have access to the right data and are getting the insights they need to be productive and make the company better every day?
If we focus on – and care about – these three things, we can handle whatever the world throws at us.
Digital Transformation & the Intelligent Era
Aren’t we all a little tired of talking about digital transformation?
You get to the point where you see it in another headline and your eyes roll back in your head. But is digital transformation still the right term for what we need to focus on? Those three key things I named above have all become digital, so I’m afraid it is!
Take the customer experience, for example. The way people buy things today is different from how it used to be. It’s important for us to have sensors along the way to understand and capture what people are doing all along their path to purchase and beyond. Employee experience has changed too, as people are more dispersed and more reliant on digital tools to help them do their jobs effectively.
We are now in the intelligent era.
AI has been around for a long time. It’s on a multi-generation journey. To leverage it before, you had to engage engineers. It was very time-consuming and specialized. Bespoke. Because it wasn’t available to everyone, not everyone recognized we were in this new Artificial Intelligence era.
Think about it: compute is practically free, storage is practically free. The barriers are being broken down to the point where, as a company, you realize that through intelligent systems is how you will win.
The general population is now catching up thanks to things like ChatGPT. The change agents know this moment is here – their challenge has been to figure out how we can get insights and make decisions from this sea of data? It’s no slam dunk, of course. If you look up research from McKinsey, you’ll see that roughly 70% of digital transformations failed. They simply didn’t meet the goals that were set at the start. Maybe change agents met pushback they couldn’t overcome or they didn’t know what they really wanted.
We know now that tech-powered outcomes are the thing to focus on. To move to the next level, we must actually use the data from these systems so we can make decisions faster, better and more effectively than our competition. Time to market always wins. Time to insight always wins. Period.
Data Democratization and Data Literacy
If we want to build a modern, data-driven enterprise, we need to start by democratizing the data we’re sitting on and making it accessible across all our teams. We’re swimming in data. But we can’t sit back and wait for our data scientists, often overwhelmed with demands, to give us exactly what we need.
So what do we do? How do we have people engage with data across the organization?
Well, let’s talk about ChatGPT. ChatGPT is not unique or new; large language models have been around for a long time. But along comes a tool that is easy to use and available to all. The minute the masses get their hands on it, that’s it! That’s the democratization of AI.
Companies have already moved on this. But they’re not trying to build it themselves – they would be crazy to do that. You can’t possibly hire enough engineers to compete with the market. Instead, you need to turn to cloud-powered solutions, harness them and use them for your own company.
The problem this creates is that we now have so many products in the cloud. CIOs are on the hook to prioritize them all and help cloud-powered companies improve their decision making. If you don’t modernize your systems with this in mind, you’ll be left behind. This is where the growth is going to be. Meanwhile, everyday employees are reading articles that say, “Hey, if you don’t figure this stuff out, you will be antiquated. You’ll be automated out of a job.” So now, as an employee, when I hear about “data democratization,” I’m all ears!
I always see surveys where CIOs rank what matters most to them. Up until a few years ago, it was always Cybersecurity at the top. Now, I see Data and Analytics in the top two or three of every survey. I think it reflects that some people were late to the data party and they are feeling this pressure that, if they don’t figure it out, their business will be disrupted.
We have to ask ourselves why more people aren’t able to participate in this new landscape. I think the simple answer is that many companies don’t have the right culture for democratizing data. They have too many controls around their data, which limits the number of people who can access it. It’s natural. When people have something valuable, they want to control it.
But we need to work to break down some of the cultural norms that keep data under such tight control.
- Companies will need to get more comfortable with a dynamic governance model.
- We need to figure out which things can be made more accessible and which truly need to be controlled.
The next step is to consider data privacy issues and bias issues. And then we need to spend some time training people on how to use data. Bad decisions can happen if people aren’t data and AI literate.
ChatGPT provides a perfect example of this: if you use it without knowing how to ask the right questions – or if you take it at face value – it will give you the wrong answers. Democratization of data can be scary for a lot of companies but, when it’s done right, it can be transformative.
Dynamic Data Governance
Corporate data flows from the CIO level on down. In most companies, that flow is marked by incredible complexity. Alteryx is no different. We have over 300 SaaS applications that comprise the backbone of our company. We’d like to get that number down and we will. But every company has gone through a best-of-breed sprawl of capabilities because this innovation was there.
In order to be a data-driven enterprise, we need to help rank-and-file employees swiftly access the data they need as quickly as possible. We need to turn them into change agents. Are people aware of compliance concerns around data? Not always. We have to be able to explain important regulatory and compliance considerations like GDPR and CCPA to them.
Roughly 80-90% of all analytics projects are data engineering–in other words, identifying, gathering, accessing, and normalizing data. The analytics piece comes at the end of that long process.
The question is, how do we make our people data-literate enough to speed up that first 80 or 90%? This is a critical and often overlooked topic. The solution is to break down some walls so people don’t waste so much time on that front end. It can be done.