The most dangerous areas on the planet are the tectonic plate boundaries. Millions of people have died as a result of their feud, and untold amounts of harm has been done. Ironically, the earth would not have evolved into the habitable world it is today if not for this friction. The commercial equivalent of the tectonic plate boundary is where sales and production operate. The pressure between these two teams can cause issues, but it also allows the company to grow.
Scenario 1: The sales team believes that demand is strong and is pursuing a variety of leads that is believed to provide result in business. It is estimated that X number of units would be needed based on those projections.
Scenario 2: The sales staff miscalculates the market for the product. Customer orders are suddenly going in all directions, and manufacturing can’t keep up. Customers are dissatisfied that their orders are delivered late, everyone is stressed, and finger pointing over who is to blame begins.
Neither of these situations would happen in a perfect world. Sales will be able to forecast potential sales accurately and adapt them to the manufacturing product build cycle. As a result, manufacturing will be able to produce product in a consistent flow that corresponded to consumer demand.
However, when it comes to material preparation, several supply chains overlook the sales outlook. These were burned by poor sales forecasts and then criticised for not providing enough inventory to satisfy demand. As a result, it continued to query sales for figures, but only use them to complement build preparation.
Sales staff are skilled at comprehending goods, determining their value proposition, cultivating customer relationships, and closing deals. In most cases, visibility into the sales cycle is insufficient, necessitating historical trending research to arrive at a precise overall figure. And trending isn’t a salesperson’s strong suit. Data analysts are in the best position to manage trending requirements correctly.
To make matters worse, sales is concerned with revenue, while supply chain is concerned with product units. As a result, what was always a difficult data challenge has become much more difficult. This issue can be found in companies all over the world.