In today’s globalized and volatile world, leading companies are looking for ways to gain better information visibility so they have more control over outcomes when events negatively impact their supply chain. Many are looking to the concept of a “control tower” that provides centralized, near-real time, granular visibility to inventory positions as well as to inventory movements. These control towers continuously aggregate vast amounts of information from the extended network of suppliers and carriers, as well as from internal company systems, to help logistics managers identify and rectify potential problems before they impact customers. Visibility into inventory positions is a big operational advantage, but in order for a control tower to be of truly strategic value to a company, it needs to also capture granular cost information in near real-time. After all, there is no point in always satisfying every customer if you lose money doing it.

Once you have granular, real-time cost information by SKU or by unit, a whole range of options open up to help you make profitable logistics decisions and to maximize customer satisfaction. For example, with enhanced visibility you might see that taking a particular SKU into a DC and then shipping it out is not as cost effective as a direct shipment to the customer (or retail store). Or you may find that an increase in the order for a particular SKU has a positive impact on profitability, even though it may mean higher inventory carrying costs, because the transportation savings more than offsets the higher inventory carrying costs. Only by fine-tuning the logistics strategy at the individual SKU or unit level can you maximize profitability while maintaining high levels of customer satisfaction.

This is especially important in an uncertain supply chain world, because as events impact the supply chain only granular visibility to inventory and cost information for each SKU will provide you the means to adjust course to keep your business on an even keel while your competitors’ wheels are falling off around them.

Historically, many companies have captured costs using a “top-down” methodology, essentially taking costs like total inbound transportation spend for a month and allocating it to each SKU based on total cases received for each SKU. The problem with this method is that it is treats every SKU the same and makes the assumption that the volume of a particular SKU handled is the sole driver of its total cost. But we know that this is often not true. Many SKUs come in odd-sized cartons or require special handling (e.g. refrigerated items), or perhaps have different duty import rates than other SKUs. These meaningful differences in costs between SKUs are hidden by a top-down averaging approach and so it’s impossible to make a decision to do one thing with one SKU and another thing with another SKU and have confidence that those decisions will have a positive impact on profitability.

All that sounds good in theory, but how do you get granular cost visibility by SKU? You have to adopt a totally new approach, one that is gathering momentum within logistics and supply chain circles – cost-to-serve measurement and analysis capability. Cost-to-serve looks at the true cost to serve your customer by taking into account all the supply chain costs up to the point that the customer takes the goods off your hands – from inbound logistics to distribution management to outbound logistics and store operations (if applicable), and assigning them to each SKU based on the relevant attribute of the SKU that drives those costs. For example, cube volume of a SKU typically drives most transportation costs but SKU value drives inventory carrying and insurance costs. And in order to get the most from cost-to-serve analysis, leading edge companies are starting to use a highly automated, bottoms-up, transaction by transaction, near real-time solution that allows them to work off the most current information that is accurate for each and every SKU.

Having an automated, granular, bottoms-up, near real-time cost-to-serve analysis solution is a defining characteristic of control towers of the future. Think of it as control tower 2.0. It’s a game-changer, because companies that can determine their true costs for any item have more options to make profitable decisions than those that can’t. And that allows those companies to differentiate from their competition and thrive in a volatile and risky world.

Frank Tomany is a Senior Director in Manhattan Associates’ Product Management organization where he is responsible for providing strategic direction for the company’s Business Intelligence and Decision Support solutions. Tomany has more than 20 years experience developing, implementing and overseeing supply chain related solutions in the Retail, Consumer Packaged Goods and Technology Manufacturing sectors. Prior to joining Manhattan Associates, he held supply chain focused leadership positions at Accenture, PriceWaterhouseCoopers, Cambridge Technology Partners and was a co-founder of Evant, a supply chain planning software company acquired by Manhattan Associates in 2005. Tomany holds a BA degree from Trinity College, Dublin.