Manufacturers are aware of the opportunities available to them under new legislation, and of the growth potential ahead. But as we previously discussed, few are prepared to capitalize on the opportunities through sales modernization. It’s an opportunity that promises to shake up the manufacturing landscape, and taking steps to establish a strong foundation now is critical.
Companies can start their sales modernization processes through focusing on the human end of things—finding the right customers, hiring the right people, and incentivizing them the right way—but to maximize their potential, they’ll need to focus on the numbers side as well. To get your organization ready for a future boom market, consider a few additional places to modernize your sales approach.
When we left off in our last manufacturing sales modernization article, we were talking about incentive compensation planning. If you’re modernizing your incentives, you’re already making an important improvement, but to get the best possible performance, you’ll need to handle territories and quotas as well. Unclear incentives, unfair territories, and unachievable quotas all can lead to employee dissatisfaction and ultimately attrition in a sales force. Knowing how competitive the sales talent market is today, we can expect that a boom in manufacturing sales will give top sellers even more options. Ensuring modern systems and processes are in place to enable sellers will be critical in retaining top talent.
Research has also shown that optimizing territories can increase sales by 2 to 7 percent without any change in total resources or sales strategy—but achieving this takes fluency in data. Modern solutions use buyer intent data on prospects, historical performance on customers, and sales team staffing to determine equitable territories and quotas for all sellers. Performance to plan can be tracked in real-time, allowing sellers complete transparency into their performance and impact to compensation.
The primary goal of a seller is to close as many deals as possible, as quickly as possible, to achieve their plan. While companies provide their sellers with tools to manage contacts, leads, and opportunities, the most successful sales organizations know they need to help their sellers pick the right approach for each prospect. Companies have usually modeled sales strategies on a few big deals closed recently, a paperback about sales techniques someone bought at an airport eight years ago, or through pure guesswork. A seller can still close deals like this, but with a large order at stake most sales leaders will want a sales strategy that maximizes the chance of winning.
Modern sales tools provide insights into sales tactics as well as strategies—like what messaging to use in a client pitch, or when to reach out to a particular customer. If you can understand what behaviors contribute most to closing deals, you can synthesize these insights to form cohesive sales strategies to improve seller productivity. A recent article by a colleague talks about this in more detail.
Just a few short years ago AI was only a buzzword, but recent technological developments have turned it into a potential productivity tool. While ChatGPT, Midjourney, and other generative AI tools have captured people’s attention with automatically generated text and images, few companies have figured out how to implement them at scale. Nonetheless, we realize the potential is there for AI to make a major impact on the business landscape, likely sooner rather than later.
As is usually the case, the less flashy innovations in AI are the most useful. Predictive AIs can’t write a Shakespearean sonnet summarizing your favorite Nicholas Cage movie like their generative AI cousins, but they can ingest massive amounts of data and return accurate predictions. Companies that used to spend weeks building their quarterly sales forecast or prospect list may soon turn the entire process over to AI, getting the first round of numbers with a single click.
Of course, any good data scientist will tell you: “garbage in, garbage out.” Deep learning models are only as good as the data they’re trained on. As a result, any company hoping to take advantage of exciting new AI developments will first have to focus on something decidedly non-glamorous: data quality. While mundane in comparison, addressing data quality now can ensure that you’re poised to take advantage of future AI capability when the time comes.
Even with these preparations made, it’s possible that the market will surprise us again. The best preparations you can make for any scenario are the ones that make you better informed and more nimble. The recommendations above may help you take advantage of a rising manufacturing sector, but they’ll also help you field whatever unexpected turbulences may come your way.
Manufacturers have tasked Spaulding Ridge with helping them prepare for growth and get ready for challenging markets. If you’re unsure where to start in your own preparations, get in touch!
