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Brooks Hamilton, founder of AI Strategy Advisors, is a seasoned veteran in the techindustry, helping businesses build and implement AI strategies.
We sat down with Hamilton to get his take on the latest in AI and its impact on distributors’ profitability and productivity. He also previewed his session at our upcoming 2024 Profit and Productivity Summit for Distributors.
Distribution Strategy Group: You’ve said that, in the past, businesses had to make a trade-off when it came to profit and productivity gains. But now, you say they don’t have to. Can you elaborate on what’s changed?
Brooks Hamilton: Historically, the two methods of driving productivity or profit were price increases and cost cutting. Many organizations are loath to increase prices; they’re not sure how to do it in a way that won’t damage their reputation in the market or slow sales velocity. Alternatively, the two major costs distributors have are capital tied up in inventory and expenses for headcount. These don’t easily allow for cost-cutting opportunities.
Additionally, there is significant complexity that goes into a distribution business; it’s essentially an information management organization. Every spreadsheet a distributor receives from a supplier is different in terms of structure, field names and product IDs, even for the same product. The hard part is managing all that data.
As distributors add more customers, products and channels, they commonly hire more people to handle the added scale and complexity. With the latest round of AI tools available, it offers opportunities to continue to grow while not having to grow headcount at the same rate. Automating and augmenting tasks like managing spreadsheets for repetitive procurement, pricing and inventory management tasks will free up time for revenue growth, improving the customer experience and making better, more informed decisions.
DSG: You have previously referenced “triples” when discussing the opportunities you are seeing for AI in the market. Can you explain what that means and how artificial intelligence products are enabling these opportunities?
Hamilton: Triples are what I call an opportunity to improve three things: profits, revenue and employee satisfaction. We have been typically forced to make a trade-off between at least one of those three areas. This latest round of artificial intelligence products enables us to find areas in the organization to drive all three improvements at the same time.
Within these three areas, we’re going to focus on pricing, sales opportunities and inventory management.
From a profitability standpoint, pricing drives an enormous amount of productivity. That might sound counterintuitive. As we know with pricing, many small changes accumulate to drive very significant benefit to the bottom line without reducing revenue. Consider the level of effort it would require to generate margin dollars equivalent to an additional 100 basis points of margin. The options are to raise prices by 1% or sell, deliver and service an additional $3 million more in sales.
Let’s say I have $100 million annual revenue with an average net margin rate of 5% (not gross margin). That comes to $5 million. Let’s assume we were able to increase prices by an average of 1% of the sales price without impacting the revenue run rate. That price change increases the net margin to 6%, since price increases flow directly to the bottom line. That is a 20% increase in margin dollars from $5 million to $6 million.
The second area is sales opportunities. Sales representatives want to look credible in front of their clients and their prospects. There is a wonderful set of tools that we can use today to equip them to know what to talk about, what to sell, how to continue to expand in the account and how to plan their day to be highly effective. No more relying entirely on “Did you see the game?” and taking an order.
The third area is inventory management. We all know inventory ties up large amounts of capital and cash and dictates how we warehouse the products available to our clients. There are great solutions to optimize the inventory we keep in stock and how we can go about making great use of our cash in terms of productivity.
The recent AI releases demonstrate tremendous productivity gains can be made within any organization. Many of our corporate functions involve pulling information from one system, making minor transformations, applying business logic and pushing it into another application or spreadsheet.
As an economy, we have created a whole set of corporate roles within departments for people who act as “human middleware.”
DSG: Tell us more about “middleware” and the role AI can play.
Hamilton: Middleware is a term used for programs that send data from one application to another on an automated schedule. This has been a necessity because, to date, our applications lacked the flexibility to configure thousands of processes, each of which differ from one another and can be different each time the process is performed. Let’s take the process of a vendor cost update.
The process is clear – update our system cost data based off the new set of prices from vendors. Unfortunately, the timing, steps and materials may differ significantly between each vendor. We may be able to define and configure a common path in software, but not all vendors will choose to or be able to adhere to it. That leaves our departments with enormous amounts of manual and semi-manual work to execute. This isn’t just your business or the wholesale distribution industry. This phenomenon permeates the corporate world.
With generative AI, we have the opportunity to revisit this assumption of the organizational pattern of the modern company.
These roles can be streamlined within our organizations. Instead of people focusing on moving data from one spreadsheet to another, they can use the knowledge they’ve learned and apply it in different ways. Many people pursue certifications outside of work to be a better procurement officer, pricer, marketer or supply chain specialist. They do this for all the right reasons – career advancement, lifetime learning and the satisfaction that comes from honing one’s craft.
Unfortunately, the crucial skills to achieving excellence at their respective role is too infrequently employed and exercises because the majority of their task work is performing, facilitating and managing human middleware work. This leads to a lack of alignment between outcomes. Shareholders and senior management need those functions to minimize inventory spend, maximize margin via price and deliver high fill rates while managing cash. Yet, the path to success — or even survival – of those same departments relies on managing data flows.
To be productive, we need to unlock the knowledge and skills already within our organization. If we can augment our existing teams with the right set of tools and information, they can spend their time driving excellent decision-making within your company. That can lead to enormous revenue, margin and employee satisfaction gains.
DSG: How would you address leaders’ skepticism toward adopting new and unfamiliar technologies?
Hamilton: I understand new techniques may appear risky. However, ChatGPT has legitimized an entire set of solutions for manufacturing and distribution that have been used in other industries for decades. Instead of exploring a large number of use cases, I suggest focusing on specific levers, such as pricing initiatives and sales opportunities, which can deliver significant value. Additionally, I recommend providing rules of thumb for expected improvements and a rubric to help leaders prioritize these initiatives, rather than endorsing specific vendors.
Distributors should prioritize areas where AI is already mature and can deliver quick wins. While chatbots sound appealing and the technology certainly exists, sorting through all that data, testing, liability issues and associated hallucinations may make it better suited for later in the roadmap.
Distributors should take a structured, methodological approach to evaluating AI opportunities to avoid focusing on projects with limited impact. Take chatbots for example. How much revenue can it drive? In my mind, it’s not a revenue builder. Well, let’s consider profitability. How much of my cost basis is going to be reduced by a chatbot?
I may not have to hire as many customer service people as my business grows. Perhaps. But how many of your customers will use the chatbot as their primary or even their secondary method of interaction with you? I’d guess not many among customers of distributors.
Instead, lean on AI tools that give salespeople insights that help them drive revenue right away while better serving the customer.
