By Drew Hofler, VP of Portfolio Marketing 

AI, ML, IoT, RPA – in today’s tech-obsessed business world, you can’t go an hour without stumbling on one of the latest tech buzzwords, likely with its very own acronym to go along with it. We hear them so often, it’s easy to forget that these intelligent technologies actually are a lot more than buzzwords. While they have hundreds of different applications, potential applications and use cases, there is one thing we can all agree on – these technologies have changed the face of business. Not just for software companies and tech giants, but for every business and industry, from mom-and-pop retail shops, to Fortune 50 companies.

In our world of business finance, emerging technologies like advanced analytics, machine learning and automation have given companies the opportunity to dramatically improve how they manage their business spend. They help CFOs make better decisions faster on where to save, how to save, where to increase cash flow, etc. Let’s take a look at a few different ways technology is enabling finance to more intelligently approach spend management.

Connecting the Dots

As finance professionals, we’re accustomed to dealing with data. Decades ago, it was through handwritten ledgers, and then Excel spreadsheets, and now we’ve moved past these to more intelligent business intelligence suites and visual dashboards. Still, we face numerous data challenges. Each department across an organization has its own data sets, and these data sets often live in silos with no visibility from one department to the other. And in fact, even if we could manually share data across organizations, there is so much of it that even the most skilled Excel whiz in your company is destined to make a human error, and certainly is not well equipped to manually manage and make sense of it all. Instead, we rely on automation and analytics technologies to cull data from across the entire organization, connect all the dots and identify patterns. In the realm of spend management, it’s critical to bring all of this data together to gain a holistic view of overall spend across the organization. We can uncover patterns, areas to increase savings, discover fraudulent or duplicate charges, understand if one supplier is being used across multiple systems/departments, etc. In short, when we can connect the data dots, we become much more strategic assets to our organizations.

Learning Based on Usage Patterns

To understand spend management, we need to also consider each different type of spend. There are indirect goods such as computers, desks, etc., as well as direct materials such as what a business needs to build whatever it is they sell to the market (think: a clothing manufacturer needing to buy fabric). But there are also workforce expenses, services expenses and travel expenses. Intelligent technologies like AI, automation and machine learning can help improve these spend management processes in many ways, by automating and speeding up the process, or by identifying patterns and make recommendations to improve efficiency and cost. For booking corporate travel, this could mean constantly monitoring external data sources to trigger alerts for better hotel and airline rates. In workforce management, machine learning helps HR find the right candidates based on similar skills and experience to past hires, and automatically filtering out resumes without the right qualifications.

Perhaps the greatest case for intelligent technology in spend management is good old-fashioned materials procurement. There are often so many corporate guard rails for what can be bought, for what price and from who, that it’s nearly impossible for a procurement professional to manually manage within the restrictions of corporate buying policies. This is where automation and AI come in, ensuring that procurement only sees approved supplier options, and learning from past purchases to pre-populate RFQs. Modern procurement platforms can also make strategic recommendations by analyzing past patterns. For example, if a supplier has requested early payments in the past, the system can detect this and automatically negotiate terms with the supplier to accelerate their payment, in exchange for a discounted rate. When so much of our job is about cutting costs, this can be a game changer for procurement.

Make Smarter Spending Decisions – Faster

The reality is there’s way too much data in the world today for humans to process. Intelligent technologies allow finance professionals to access the mountains of data available to them, in a usable, fast way. Humans simply cannot digest this data in real-time, let alone analyze it for patterns and make recommendations. We need automation and data management technology to sift through it all, AI to detect patterns, and machine learning to continually improve and recommend better options/processes. With these technologies at our fingertips, we have more insight into the reality and the causality of the numbers that are more important to us. This makes data more actionable, and timely – and makes us much better at our jobs. In the past, CFOs didn’t know if their sales or revenue numbers were off until EOM or EOQ. Now, they can take action quickly where they need to, making changes to help them increase ROI before it’s too late.

As finance professional we’re constantly being tasked to make critical decisions on spending, revenue goals, sales numbers, cost-cutting and the list goes on. While there will always be new challenges, especially as the amount of data we manage continues to grow, applying intelligent technologies allows us to make more strategic, informed decisions to positively impact the bottom line.