Reduce the Noise Around AI: Think ‘Fit’ First for Your Distribution Business - Modern Distribution Management

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Reduce the Noise Around AI: Think ‘Fit’ First for Your Distribution Business

When making a business case for AI and evaluating its fit in your distribution business, you should consider asking these essential questions.
MDM-Reduce the Noise Around AI

The purpose of technology has always been to achieve a desired outcome with less effort, faster, and usually more effectively.

But the rapid evolution of technology presents so many choices that it can be overwhelming. Viewing technology as a magic solution for your business challenges or an overly complex burden is easy.

But if we simplify the technology away from software, the lessons that we can learn become clearer:

  • In construction, just because a team wants to build houses faster does not mean they will buy any tool they see – they first consider whether they will have a use for it and how much better it is than the current tool they are using.
  • In sports, athletes evaluate gear based on whether it feels good and is right for them. They try it on and try it out, all with the intention of ensuring it improves their performance.

AI and distribution make sense combined, and distributors feel the pressure to start. But before committing to an AI tool, you must determine whether it is the right fit for your business.

Focusing on fit is a great way to reduce the noise around AI and simplify the selection into something that can fit on your already crowded plate. Your day-to-day responsibilities are stressful enough without trying to wrap your head around AI at the highest level. But if you narrow AI to what applies to your company’s needs, any knowledge gaps you may have will be much easier to bridge.

Editor’s Note

You can learn much more about distribution AI from Nick Pericle at MDM’s 2024 SHIFT Conference — set for Sept. 11-13 in Denver — where he host a ChatGPT workshop.

When assessing AI technology, consider three types of fit:

  1. Business outcome
  2. Process
  3. Technology

Business Outcome Fit: Will the tool help you achieve your company’s goals? Are you hoping to increase revenue, reduce costs, improve customer experience, or increase efficiency? AI tools can align with these goals, but not all will be useful across the board or may have equal weight in your organization’s priorities. If you choose a broadly powerful tool that lacks the granular capabilities to help drive your primary desired outcome, you may be disappointed in the ROI.

Process Fit: This is how well the AI tool will integrate with your existing business processes. After all, adopting AI should make work easier; if you have to significantly adjust workflows with process scaffolding just for a tool to function, it defeats the purpose.

Instead, thoroughly investigate the tool’s compatibility with how your company makes decisions and gets things done internally and externally. Ideally, your chosen solution will integrate cleanly with those processes, making them more effective and efficient.

Technology Fit: Is the tool a good fit with your existing and intended future technology stack? Implementing an AI-powered tool does not necessarily mean a total tech overhaul — not only will that drive up costs, but it can also threaten your team’s ability and desire to fully adopt your chosen AI solution. Instead, look for tools compatible with your current systems and software platforms. This will keep your implementation costs down while allowing your team members to continue using the programs they’re familiar with and comfortable with.

Technology fit is particularly important because it forces you to consider how technology will affect your business’s future in the here and now. By choosing an AI tool that fits snugly within your company’s existing tech infrastructure, you can ensure that it will scale, grow, and adapt to your business.

You can also maintain flexibility and scalability, ensuring that each component or service can be upgraded or replaced while minimizing disruption. This strategy promotes operational agility and protects against risks like vendor lock-in, ensuring that AI solutions can evolve as your business needs change.

It’s critical, however, to take time into AI adoption merely to keep up with trends or competitors. Instead, take a measured approach, considering how each AI solution aligns with your business objectives, processes, and existing technology stack. By doing so, you prioritize strategic fit over convenience and ensure that your AI investments are impactful and sustainable.

Making a Business Case for AI: Questions to Ask Your Team

As your organization considers each of the above “fit” aspects, I would encourage you to consider the following questions with your team when putting together a business case for an AI tool.

Business Outcome Fit:

  • How will this AI directly affect our key performance indicators?
  • Does the tool address our specific business pain points?
  • Can we align and measure the tool’s effects against our strategic goals?

Process Fit:

  • How will this AI integrate into our existing workflows?
  • Does it simplify or complicate our decision-making?
  • What training is required, and do the expected improvements justify it?

Technology Fit:

  • Is this AI compatible with our current technology stack?
  • Will it make our infrastructure more future-proof?
  • How well does it integrate with other systems to enhance functionality?

While the pressure to capitalize on AI is real and pressing, the key to any successful technology implementation lies in not being reactive. Instead, take the time to thoroughly assess how each potential AI tool fits within your organization. This strategic patience will help you avoid common pitfalls and turn AI adoption from a possible source of stress into a significant competitive advantage. This also ensures that your investment in AI moves your organization forward meaningfully.

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