The economic headwinds of 2023 have sent consumers and businesses alike through the wringer. The economy has cooled, budgets have tightened, and decision-makers at every scale—family households, small businesses, or global enterprises—have to now make strategic, thoughtful choices about their investments to secure a healthy, long-term future through uncertain times.
We recently sat down with Kevin Willemse, Director in Simplus’ Advisory Services practice, to get his insights on the cool economy we’re living in now, where businesses are going from here with their technology investments, and what role the excitement surrounding AI has to play in all of it.
Can you address the current economic climate at a macro level? How did we get to where we are today?
I think we’re still coming out of the COVID hangover. If you look at a lot of the investments that companies had to make in new technology, business processes, hiring of people… that was a reaction to what was going on then. And some of those investments have paid off, and they’ve used that to streamline their businesses into their current operations. But some were throwaway investments that they’re now having to deal with, and that just causes a restriction in budgets all around. So now you’re looking at how to recover from that, how to leverage what they’ve invested in, and so on.
What trends do you see coming from business leaders as a result of this climate?
Business and IT often have different views on how to react. On the business side, we’re seeing a lot of business leaders wanting their vendors and suppliers to be more strategic and holistic in how they look at their business and ultimately how the investments that get proposed are truly going to transform large or small parts of their organization but also drive true value. It’s not just about transformation or change for change’s sake. They want to see how you’re going to realize that value, how you’re going to measure it, and why you’re prioritizing focusing on that particular investment…They’re getting more specific in terms of identifying where their problems are and then putting out to market to say ‘As a business owner, this is the change I want to see and you need to really prove how you’re going to address that.’
From an IT side, it’s a little bit different, and I’d say the message there is that they want to do more with less. They want to do more with what they have already. So when they’re looking at their current architecture and application stack and challenging vendors and SIs, they say ‘How do we make sure that this investment is a good one for us, how can we rationalize it out, how can we squeeze value out of these things that are currently sitting on our books, and what can we actually get rid of before we even look at bringing on new technologies?’.
Artificial Intelligence is making a lot of waves in the media right now. Everyone is focused on the distant potential of this technology, but how do you think this will factor into businesses in the short term?
There have been, in the near and short term, organizations that can capitalize on it right now and have done so successfully. But there are also a lot of instances where there are less successful endeavors into the world of AI by companies that didn’t look at the utility for their particular use cases. So in the short term, I think you’re going to see a lot of sudden emergence that has really helped businesses but you are going to hear a lot less about those that have looked at it, tried it, and deemed it not valuable, not relevant, or ultimately failed. So that’s going to continue to drive the hype for a little while. I think the key is to realize that it is new, don’t get caught up too much, keep it as part of your ultimate toolkit, but be very careful in terms of how and when to deploy or actually start investing in it.
What can business leaders do to prepare for the advent of integrated AI in the workplace?
I would say that preparing for integrated AI in your workplace for a business is the same as preparing for any change or opportunity that comes your way. You’ve got to look at that very pragmatically in terms of does that have a place, would it work, is it actually influential to your business and your way of operations, and so on. You’ve really got to come to a conclusion if this is something worth looking into further. If the answer is no, don’t ignore it of course. It’s still going to continue and grow, and there might come a time when it is more relevant. So don’t push it to the side too much.
If the answer is yes, go further. A lot of folks, if you’re on the human side, they’re worried about how it’s going to displace people in the workplace. If you’re going to invest in AI, make it clear what your strategy is, why you’re doing it, and syndicate that within the organization as part of your strategy and how that might impact operations, people, and your technology overall. The other side of it is data. AI is nothing without data, that’s just a simple fact. And very often, while you might have all intention to capitalize and make your business better, if you don’t have the constructs and the diligence and the structures in place to really start monitoring, gathering, and trusting your data, you’re never going to get anywhere. So those are more on the practical side of the things you’ve got to look at, even if there is an opportunity in your workplace to transform and make it better. If you’re going to decide on that, you’ve really got to start checking the boxes in terms of what it takes to get there to start delivering the value and meeting those expectations that you have for it.
So many organizations have heavily invested in their tech stacks. What can they be doing to first get the most out of what they have before adding or replacing platforms?
The first thing you’ve got to do is understand how and when and why and by who that technology is being used. That means going to your business users and mapping out what they’re doing, what technology they’re using, and what the intended outcome is of using that technology in terms of facilitating that process or making it more efficient. This isn’t a requirements-gathering session, it’s not a design session. It’s just purely understanding what their experience is—good, bad, or anywhere in between—of using that technology and where the major gaps are as well as where there are overlaps, two pieces of technology that could potentially be doing the same thing. Then taking that view of the end-to-end business processes and saying, ‘How does that technology map out?’ and ranking those applications based on how they’re actually supporting those business processes.
One of the key things you tend to find is it’s often not a failure of the piece of technology or application, it’s just in the way it’s been implemented. There might be a particular configuration or some customization might need to be done on it. So call on your product vendors and your integrators and your consultants to work with them and say ‘How do we plug these individual gaps?’ and squeeze out the true value add from that technology investment you’ve made. Now the other thing you have to remember is sometimes you might have to concede certain current ways of doing business that are actually driving inefficiency in the technology, in the application itself. So to counter the way people like to work, they’re compromising that piece of technology or the data it’s gathering. So be prepared for discussions with those business leaders to say well this is more of a process or organizational change management effort that needs to be taken on in order for the application to work the best it can and maximize the investment in the application itself.
As Kevin wisely said, “AI is nothing without data…if you don’t have the constructs and the diligence and the structures in place to really start monitoring, gathering, and trusting your data, you’re never going to get anywhere.” But Simplus’ dedicated data and integration experts can make sure you do get where you’re going. Our team has both the experience across industries and the expertise of taking business technology transformation from start to finish, time and time again. Reach out to start road mapping your vision for a data and tech stack architecture today.