Today, a business disruption can stem from just about any type of event — a once-in-a-lifetime pandemic, economic pressures, critical skillset shortages or changes in market or investor evaluation criteria. Only resilient companies can ride out the turbulence and quickly bounce back.
But with the ongoing pace of change, making your company more resilient may seem impossible. With that in mind, SAS asked business executives how prepared they think their companies are to face unexpected challenges and if they are working to incorporate resiliency into their company strategy.
In the resulting report, we identify five rules that resilient organizations rely on:
- Speed and agility. Quickly adapt to changing market conditions.
- Innovation. Use data-driven insights to accelerate advancements.
- Equity and responsibility. Ensure ethical standards are applied during the design, development and use of transformative technologies.
- Data culture and literacy. Build a data-driven culture across the organization.
- Curiosity. Inspire exploration that fuels innovation and growth.
I’m going to zero in on two of those rules: Speed and agility, and innovation. If you ask me, if you want to follow those rules and invest in resiliency, you must invest in your data.
Focus first on the foundation
Years ago, the mantra was “garbage in, garbage out.” That saying is still sound. If you don’t have a solid data foundation, you can’t know that the decisions you are making today are the right ones. To make your organization more resilient, and better able to respond to disruption, you have to start with data management.
I'm happy that data management has become fashionable again. We’ve been riding the wave of machine learning, artificial intelligence and other unbelievably groundbreaking technologies. If the foundation of your house isn’t solid, however, then the rest of what you build won’t work – and the market hasn’t focused enough on that. If you start with unorganized data, then everything else downstream is affected. You have to know what the data is and how it influences your decisions.
That foundation is critically important from a cost perspective, too. Moving data into the cloud costs you almost nothing (for good reason – cloud providers want your onboarding to be as frictionless as possible). But when you want to move data out of the cloud, it’s very expensive. So about 10 years ago, SAS pioneered running analytics in the cloud, and we’ve been continuing innovations there ever since.
One of the things AI is great at is taking on mundane tasks and freeing up humans for creative problem-solving. AI is going to do the same thing for data management. That's going to be groundbreaking over the next couple months.
Is AI the secret to resiliency for your company?
In the report, respondents who scored high on resiliency prioritized AI and analytics to navigate disruption. But some companies still aren’t buying into the promise of AI and other emerging technologies. And maybe that’s understandable. For a long time, AI has been a technology looking for a need instead of the other way around.
But when we think about how digitally and analytically mature some of these companies are, we have to start with the basic blocking and tackling, which is what I mentioned at the beginning. You have to have sound data management and analytic practices in play, and then you can start to scale them – not the other way around.
One of the other pieces of AI advice I always give SAS customers is: Go pick a use case that is actually important and relevant to your business. For example, in the early days of AI chatbots, we’d see companies deploying chatbots and using AI technology internally. I know it’s interesting, but it’s a waste when you could have been using the exercise to learn something useful for your business. Instead, find a problem that’s meaningful to your business, scope the problem, and then bring in the technology to solve it.
There are a couple different approaches you can take.
- The Big Bang approach. Find the biggest, hardest problem you have and attack it. With enough executive support, time and money, your team and AI will be heroes.
- The controlled explosion. Find a problem that you can get your hands around; choose a small group of engineers, developers and data scientists; and quickly show tangible results. Now, your team and AI can hand-pick your next projects.
When we talk about disruption, the “controlled explosion” group are the people getting disrupted. Those people can identify a problem, apply technology to it and make a decision in a week. Those are the people who are going to adapt to the next supply-chain-like problem when it goes upside down. You can't take six months to solve that sort of crisis. You have to find a problem that means something and is manageable, solve it, and then go scale it.
Just remember, AI is just one of the tools in the larger toolbox of analytics.
At SAS, AI capabilities are integrated into our platform. We don’t want our customers focusing on the AI component. We want them to focus on the problem they need to solve and the outcome they hope to achieve. We will help them find the right tools and technologies to get there.
Planning for a more resilient future
When we think about becoming more resilient and the ability to respond to disruptive events, too often we look in the rearview mirror for a template: COVID, supply chain disruptions, the recession, etc. But we're getting to a place with simulation technology where we can learn what we're going to need to respond to in the future.
That allows us to address problems that affect our future business, not yesterday’s business. To me, that's a very exciting use of technology. That technology? Data. AI. Analytics.
My advice to you? Don’t wait. Get your data management foundation ready now. Change and disruption seem to be here to stay.
