Try to name every Apple product.
The chances are good you were able to name most of them. That’s largely because of a decision Steve Jobs made in 1997 to radically simplify Apple’s product offerings. At the time, he was frustrated that product complexity made it difficult for him to know which product to recommend to friends. That one decision dramatically changed Apple’s trajectory; enhanced focus enabled the company to be more innovative, and simplified product lines reduced component and supply chain costs. The Apple we all know today only exists because the company successfully picked the right product lines to cut.
Unfortunately, not every company can simplify its product line down to a handful of offerings. For example, the industrial parts supplier McMaster-Carr boasts a catalog of more than 500,000 parts. Their customers rely on them to carry a wide variety of products like screws, wires, and ball bearings that meet their unique needs. Trimming this catalog down to a handful of offerings without sacrificing the majority of their revenue is impossible.
How do companies like McMaster-Carr keep costs low while maintaining a diverse set of products? The answer is a mix of strategic procurement and data science.
The role of procurement
“Reducing costs” is the activity most often associated with procurement. After all, who else is going to make sure customers can afford the product ideas that come out of engineering?
The truth, though, is that procurement’s role spans far beyond cost negotiation. Procurement is responsible for balancing cost, quality, and availability of supply. Achieving this objective requires that the procurement team be closely engaged with all areas of the business. For example, procurement must be ready to lead if product proliferation is making it difficult to negotiate favorable terms with suppliers. Procurement also plays an important role if the company needs to change its supply base to improve product quality.
Procurement at Nike
One example of the broad role of procurement can be seen at Nike. As sustainability becomes a key priority for the company, procurement’s role is becoming even more far-reaching. Nike has devised a set of indicators that not only consider cost, quality, and availability of supply, but also factor in the likelihood that a supplier might not be able to perform to the company’s sustainability standards. In order for Nike to be successful, it must maintain a close eye on all of its suppliers.
This problem is particularly challenging for a company like Nike, which has thousands of suppliers. It is too expensive to have a commodity manager monitoring every one of the suppliers. Instead, companies must rely on internal and external data streams to manage a complex supply base.
Data science at McMaster-Carr, Target, and beyond
Even before the Harvard Business Review named “data scientist” the sexiest job of the 21st century, procurement managers have been using data about transactions, suppliers, and markets to make decisions. The scale of this data is non-trivial, and continues to grow. Procurement teams must increasingly lean on internal analytics teams to help them manage this information overload.
Let’s revisit the example of McMaster-Carr. Every one of their 500,000+ parts contributes a different amount of profitability. Calculating this profitability is more difficult than simply subtracting the manufacturing cost from the sale price. Factors such as inventory cost, the cost of customer support, and warranty costs must also be considered. In other words, if the company sells a product that costs $5 to manufacture for $10, but has to spend $20 answering customer service questions about the product, it might be better off eliminating that product. This concept is called the total cost of ownership and is a core aspect of analysis in procurement.
Calculating total cost of ownership by looking at historical data is insightful, but it does not necessarily reflect how costs will change going forward. In order for procurement teams like McMaster-Carr’s to make the right decisions about what products to eliminate, or how to modify their supply base, they also need to consider demand and material cost forecasts.
Target learned this lesson a couple of years ago when it realized that its underperformance was partially due to sacrificing quality too much for cost in its private label brands. The company began focusing heavily on cost during the recession in 2009, without considering future implications of its decision. As the economy improved and consumers began migrating back to higher-quality offerings, Target found itself in a bad position. The company has recently shifted its procurement strategy to increase the importance of quality—but only after it paid a high price.
Decision-making using total cost of ownership
Understanding total cost of ownership to drive optimized decision-making requires pulling from almost every data source imaginable—from internal ERPs to market intelligence data with cost forecasts. These types of analyses have typically taken weeks or months, but new technologies from companies like Tamr are greatly simplifying the process. The Tamr platform is a data preparation toolkit for teams looking to conduct a total cost of ownership analysis across a broad product line. It enables analytics teams to perform new procurement analytics as business needs change.
Balancing cost and quality
The stakes for procurement teams to correctly balance factors such as cost and quality are high, but so is the potential impact. For instance, the health care company Novartis was able to save more than $1billion through procurement initiatives, and Unilever identified more than $500M in potential cost savings opportunities by reducing stock-keeping units (SKUs) by 30%.
As economic uncertainty grows, more companies will be looking for ways procurement can drive cost savings to offset lackluster growth in revenue. If you’re part of an analytic team looking for projects to justify an investment in new capabilities, or if you’re simply looking for high-impact projects that make use of interesting data—try meeting with procurement leaders in your organization to understand how they’re managing increasing complexity. It could be exactly what the company needs to become the next Apple.
This post is a collaboration between O’Reilly and Tamr. See our statement of editorial independence.