Future-proofing operations with AI-powered predictive analytics

The COVID-19 pandemic has had a huge impact on the operation of enterprises of all sizes. Many companies have needed to make difficult decisions concerning matters such as laying off staff, establishing policies for remote work, dealing with health-care benefits, and so on. The problem is that making decisions in these areas can have a long-term impact on your business operations. Effective decision-making nowadays requires examining huge amounts of data across broad swathes of your company’s operations, and it’s possible that AI can come to the rescue in such situations. To understand how this can be, I recently chatted with Rico Burnett, the global director of client innovation at Exigent, a global services organization with over 500 employees in locations from Cape Town to Chicago. Exigent specializes in offering solutions involving AI-powered predictive analytics, and the following is an excerpt from my conversation with him.

predictive analytics

MITCH: Rico, concerning the phrase “AI-powered predictive analytics,” what exactly does “predictive analytics” mean, and how does AI fit into the picture?

RICO: Predictive analytics is the next step in the value cycle. Analytics is really about the existing structure of your information or data and allows us to make sense of what has happened. “Predictive” analytics tries to anticipate what will happen next. In that sense, it really shifts the focus from a reactive snapshot to an interactive decision-making tool. Artificial intelligence then brings efficiency and accuracy at levels that make analytics a lot more appealing than the traditional approach.

MITCH: What do you feel are some of the tough decisions businesses face in these present times?

RICO: We’ve seen some really tough choices being made on suspending or pausing digital transformation or migration in business. The cloud starts having less of a silver lining when there are increased financial pressures on the business at large. Big tech projects aside, there has been a steep drop in appetite for experimenting with new tech or piloting some new products. This means that many of the great ideas and potentially groundbreaking new products or tools that could shape the landscape will struggle to get out of the starting blocks due to the current crisis.
MITCH: How have businesses typically handled such decision-making in the past?

RICO: Typically, it has been handled with a comparative analysis. Businesses consider legacy projects to estimate the value / ROI of the next project, for example, how projects of a similar size or scope were handled or what was the scope drift like. The difficulty is that no two projects are ever the same. In some of the worst cases, it’s been a prioritization based on cost or perceived complexity. Handling technology projects in a queue like this are problematic and, given the experience over the last nine months, needs careful redesign. The decision matrix that most businesses have deployed is also under immense pressure. Previously, a project sponsor and development signposts were almost everything that you needed. Today, there are multiple stakeholders and frequent ROI presentations to contend with. Many businesses are simply not geared towards these additional requirements, and they often choose not to even start a project than see it get mothballed due to external pressures.

Business analytics trends
Freepik / Katemangostar

The difficulty is that no two projects are ever the same. In some of the worst cases, it’s been a prioritization based on cost or perceived complexity. Handling technology projects in a queue like this are problematic and, given the experience over the last nine months, needs careful redesign.

MITCH: How can using AI-powered predictive analytics help businesses make better decisions?

RICO: Predictive analytics empowers nearly all stakeholders with the necessary visibility to not just make decisions but also to adjust their vision where necessary. The decision hierarchy in many businesses is often crippling, despite being a safeguard, and we need to use all available mechanisms to reduce the cycle times. If a business is able to get a picture of what Day 90 could look like based on the information we have on Day 1 and see how that picture shifts over time, decisions become more certain and are made faster.

AI-powered analytics has another key benefit. It’s not just about what is true for your business. AI-powered analytics can also draw insight from your industry, your region, and your competitive landscape. AI-powered analytics has another key benefit. It’s not just about what is true for your business. AI-powered analytics can also draw insight from your industry, your region, and your competitive landscape. This means we are moving toward the development of “true” or accurate industry standards, which will act as clear benchmarks for performance. That is the true measure of analytic success in our view.

The decision hierarchy in many businesses is often crippling, despite being a safeguard, and we need to use all available mechanisms to reduce the cycle times. If a business is able to get a picture of what Day 90 could look like based on the information we have on Day 1, and see how that picture shifts over time, decisions become more certain and are made faster.

MITCH: What industry areas can benefit the most from using AI-powered predictive analytics?

RICO: Nearly every industry area can benefit because of the impact on decision-making speed and approval processes. For example, the legal industry has lagged behind other regulated industries like insurance and banking. If you consider the relative silos in which legal teams function within a business, predictive analytics becomes a powerful tool to play a more proactive role in commercial decision-making. We believe the most fruitful expansion for the use of AI-powered analytics to be in the higher volume / moderate risk space. These are often ignored or glossed over due to the effort required in creating a detailed analysis, but it really is here that analytics can bring about massive change. The true winners will be those businesses that build their analytics strategy to be inclusive. Data isn’t just locked up in contracts or supply chains. It spans across the business. Drawing on the legal, supply chain, finance risk, and compliance data will deliver the most meaningful and enduring return.

MITCH: What does Exigent bring to the table in this area?

RICO: Exigent has lived the entire experience. We started as an outsourced services business, bought a technology company, built our own technology, and specialized in legal technology consulting. Our innovation team, the “Mind Factory,” brings together data analytics, mathematics, audit, and legal experience. This makes us somewhat unique and allows us to present multiple perspectives for any business we work with. We don’t simply shove our products or services down a client’s throat. We take a commercial-pragmatic approach and design solutions that leverage our clients’ existing technology stack, our own solutions (where relevant), and the best third-party applications out there. This means that we are trusted as commercial advisers and not just a business value add.

MITCH: Rico, thanks very much for explaining this to us.

RICO: You’re most welcome.

Featured image: Shutterstock

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