Artificial intelligence is a hot topic in every industry right now, and distribution is no exception. While the promises of efficiency and time savings may tempt you to immediately adopt AI, it’s important to stop and consider your company’s goals and the potential pitfalls before investing in this emerging technology.
Here are seven common mistakes to avoid as your distribution company considers AI adoption.
Mistake 1: Ignoring AI technology or putting it off as a “next-year” initiative.
It’s always easier to take the path of least resistance and keep doing things the way you’ve been doing them for years. In the past, the distribution industry has tended to lag in technology adoption, in part because industry-agnostic solutions often struggle to meet the specific needs of distributors. Today, many distributors are moving toward digital transformation and data management, and it can be overwhelming to think about adding new AI solutions on top of everything else. However, the longer your company waits, the more time you’ll lose to competitors who are investing in it now.
Mistake 2: Allowing everyone to use AI tools at their own discretion.
If you ignore AI, you won’t be informed enough to offer guidance to your teams about which tools to avoid, which ones are helpful and how to use them.
Instead of having consistent adoption across your company, you’ll have a few AI champions who might be seeing some great results, but no formal processes for everyone else to follow to replicate them. Without knowing which solutions to use or the best ways to use them, newer employees or technology laggards will only fall further behind.
You don’t need to become an expert in machine learning and data analytics but take some time to broaden your understanding of AI and its use cases in the distribution industry. Seek out webinars and industry reports to hear specific examples of what’s working. Foster an AI-ready culture by encouraging your team to experiment with using generative AI tools like ChatGPT for simple, low-risk tasks like drafting emails.
Mistake 3: Investing in a stand-alone solution that doesn’t integrate with your CRM and BI software.
While AI has the potential to directly impact your company’s revenue, the solution you choose needs to work with your existing solutions, including your ERP, CRM and business intelligence software. This ensures the AI models can be trained with the data that already lives in your system. Using an integrated solution also makes it much easier for your team to act on the recommendations as they’re completing their daily responsibilities, such as checking in with customers over the phone, sending emails and creating quotes.
Mistake 4: Adopting tools that are difficult for your sales team to use.
Many distributor sales teams are accustomed to using a CRM to manage customer outreach. They may also have access to their company’s ERP but may not use it as frequently. Marketers often incorporate additional platforms to manage advertising, email marketing and other outreach efforts. When you’re adding AI tools into the mix, make sure you choose solutions that are intuitive to use and, if possible, accessible within the software they’re already using. This will shorten the learning curve and increase user adoption so your team can see a better return on your investment.
Mistake 5: Implementing a solution without a clear objective
With all the hype surrounding AI, some business leaders feel pressured to jump on the trend without evaluating their objectives. Instead of implementing new technology for technology’s sake, work with your leadership team to identify areas where AI will have the greatest impact.
Many teams look at AI solely for its potential to increase efficiency, which may be a natural first step. But saving 10 hours a week is only valuable if your team is actually spending that time on revenue-generating activities.
The good news is that there are plenty of applications for AI in distribution that do lead to revenue gains. Analyzing customer purchase data to make better recommendations for related products and maximize upselling is just one example.
Mistake 6: Giving up on an AI solution after a few months without adequately training the model.
You may be skeptical about the potential of AI, or maybe you’re expecting too much from a new solution. Either extreme can lead to giving up after only a few months. Remember that the accuracy of any AI model depends on the quality of data you use and the amount of training the model receives.
If you aren’t regularly providing new, updated data, the insights you receive won’t be timely or relevant enough to meet your objectives.
Mistake 7: Trusting your data to a vendor that doesn’t have a proven track record.
While ChatGPT and other large language models are making AI more accessible to the general public, the truth is, AI itself isn’t new. Seek out companies that are established in your industry and have a long track record of dependable results. Many software companies are adding AI tools to their existing products, making it easy for you to give this new technology a try. Look for details like when the company was founded, whether it has a documented data security and privacy policy, whether it uses a closed or open-source AI model and how robust the technical support is.
Whether you choose to start small or adopt AI tools across functional areas of your business, it’s helpful to keep the technology in perspective. AI is a tool, and like all tools, it should have a specific objective. Start with an objective that will have the biggest impact and be willing to commit to a long-term initiative. With the right focus and the right technology, you’ll be amazed at what your team can achieve.
Helen Piña is the VP of Marketing for White Cup. With a powerful CRM that empowers team members to act on their best opportunities faster, business intelligence solutions that transform customer and product data into crystal-clear insights and precision pricing software, White Cup helps distributors shift from reactive, siloed customer interactions to proactive, collaborative growth strategies. White Cup’s new AI-powered features also help distributors take their next best action. Learn more at whitecupsolutions.com.