A manufacturer was growing revenues and still struggling to stay profitable.
One of our CFO partners was brought in to work with the CEO to understand the problem and develop and implement solutions. The first focus was to dive into deep data analytics to understand unit selling price increases by sku and unit cost increases by sku over the last three years. By understanding the trends, our partner had the data to support taking action to increase selling prices where margin on products had deteriorated over time.
The results of the data analytics were enlightening in that revenue growth was coming from products that were marginally profitable, and much of the pressure on profits was a result of our largest customer. The Company was losing money on a fully loaded cost basis from its largest customer. This analysis gave us the backup necessary to negotiate a price adjustment with our largest customer. It also gave us the confidence to increase prices across the board on all products.
As a result, we ended up eliminating the sale of certain highly specialized, high volume, low margin parts for our largest customer (because of the volumes our customer was able to offshore the manufacture of those specialized parts and maintain their old unit costs). On average we ended up increasing all our unit prices by 11 %. Because we had the data to back up our price increases when we explained the increase to our customers, the only business we lost was from what was our largest customer. We were able to pick up unit volumes from other clients that we turned down before because our capacity was being consumed by these high volume, specialized and low margin parts.
End result, we were able to quickly replace the lost revenue and increase our overall gross margin by 10 points which dropped to the bottom line.