Almost a year ago, I posted a blog titled “The Case for ‘Revenue Performance Management’ in the Front Office” where I introduced this new category of performance management targeted to the unique needs of the Front Office, line of business users who control the top-line for a company.
I believe there is tremendous opportunity in delivering Back Office-like performance management techniques to the Front office to enable better business decisions by the lines of business, so I reached out to SignalDemand, one of the companies I mentioned in my last post, to test whether the framework I had developed has mapped to their experience on the ground. I also wanted to verify what type of business results companies were seeing when they deployed advanced mathematical modeling and statistical analysis to predict the future, and make rigorous decisions based on those predictions-versus the traditional approaches of analyzing history, or worse, relying only on qualitative assessments.
SignalDemand in turn shared one of their case studies from Cargill Meat Solutions, a leading processor and distributor or fresh and prepared beef, pork and turkey with more than $15B in revenue and over 35,000 employees.
In my previous post, I noted six primary areas of difference between Enterprise Performance Management and Revenue Performance Management. These differences both define the significance of the opportunity in the Front Office as well as why this large market opportunity is going to be driven by SaaS-based solutions that provide real-time answers, targeted to the needs of the line of business.
Why SaaS? It’s Not Just a Deployment Approach
In the Front Office, Line of Business managers are in charge but in many cases they lack access to the technical personnel and expertise required to design, deliver and manage the applications they need to run their organizations. Instead, you have the teams that control the top-line of the business using arcane tools such as spreadsheets and email to manage complex processes that lead to critical business decisions required to run their organizations.
Nowhere is this pain felt more acutely then around the problem of ‘price’. According to SignalDemand, this was the situation Cargill Meat Solutions (CMS) found themselves in, recognizing that their traditional means of pricing — a complex process that involves pricing experts working with internally developed tools — while serving them well in past, would not keep them competitive in the future. CMS recognized the value that could be achieved by applying predictive analytics and optimization to price back in 1999, but quickly realized that without the capability to translate price changes into their resulting revenue and supply implications, the usefulness of the technology was limited.
It wasn’t until SignalDemand brought the right mathematical modeling expertise, along with a SaaS based solution that CMS was able to get the business answers they needed. In addition to requiring targeted answers to business problems, CMS needed them to be delivered without a protracted IT project, the kind of solution that only SaaS based applications can provide.
The Dynamic Nature of the Front Office
In the Back Office, every effort is made to stabilize business processes, but in the Front Office, change is the norm. The Front Office of a company must be able to quickly adapt and adjust to change. CMS faced a situation where more than 150,000 pricing decisions were being made each week – this in an environment where they were surrounded on both the buy- and sell-side with changing market conditions. And the impact of price in this environment wasn’t isolated to sales.
There was the reality that a single production input (an animal carcass) can yield thousands different products (cuts of beef), and every carcass harvested has the same parts-so you had better use price to make sure you’re selling the various parts at the same rate, or you could end up with a lot of inventory sitting around for one part of the animal while you’re going gangbusters in another (the adage in the industry is “sell it or smell it”). In this type of environment — with significant volatility and complexity — an environment extremely common in commodity based value chains, it is nearly impossible for human intuition and spreadsheets to truly optimize an organization’s business results.
Real-Time Answers Critical to Front-Office Success
The Enterprise Performance Management tools provided by application leaders are often designed around the batch processing of data, where response time is important, but if a report takes a while to run the impact is an inconvenience rather than catastrophic to the business. Not so with Revenue Performance Management and the needs of the Front-Office.
CMS needs to be able to price-product in real-time as highlighted by Mark Hoekstra, Pricing Manager, Cargill Pork Retail, “SignalDemand has helped us to speed up our pricing process, allowing us to respond to our customers’ requests more quickly and ultimately to win more business.” The Front Office needs solutions like those delivered to Cargill which support decisions at the speed of business, with capabilities such as rapid scenario analysis, enabling a sales rep to understand the immediate price and margin impact of changes in input costs or sold position.
Revenue Centers — More Difficult, BUT More Opportunity
The reality is that it is far easier to analyze back office processes and to ensure that all costs are contained. The Front Office is more difficult because of the dynamic nature of their decisions and processes, which calls for real-time information — I’ll discuss this in more detail later. Better support for the Front Office however can have a much larger impact on a company’s bottom line as evidenced by the often quoted McKinsey study which showed that a one percent improvement in price increases operating profit by eleven percent, whereas decreasing COGS by the same one percent results in only a seven percent impact on operating profit. While the privately held company would not share financial results, they “clearly were substantial” as quoted from an AMR case study prepared on the SignalDemand deployment at Cargill. Below is a graph of information they did share with AMR, showing two measures of CMS price volatility, both before and after implementing SignalDemand.
The Executive Champion: A Critical Role in Front Office Success
In the Back Office, it is likely you must use an application to accomplish many, if not all, aspects of your job while in the Front Office; just the opposite is true — other than a few applications (e.g. email), you may only interact occasionally with an application to accomplish your objectives. When asked how they managed the “change management” elements of the project, project sponsor, Herb Meischen, noted that it was the president of Cargill Meat Solutions who sponsored the project and that this senior sponsorship helped facilitate the product’s rapid adoption. User adoption can be a challenge when organizations are accustomed to using “gut feel” and intuition rather than mathematical models. Meishen points to the fact that Cargill initially ran the technology in parallel with what was then a spreadsheet-based method to determine price. From AMR’s case study on Cargill, “Each day, the SignalDemand technology calculated pricing options and the best mix, while the team used existing processes to calculate pricing options manually. When team members found out the technology could more accurately price a complex scenario in minutes versus the manual process of hours or days, they quickly adopted the tool.”
Applying Predictive Analytics to the Front Office: Turning Subjective Data into Objective Data
By far the largest difference between the Back Office and Front Office is that with relatively few exceptions, the Back Office is driven by objective data and decisions can be made at a relatively slower rate. In contrast, the Front Office is largely driven by subjective data and the decisions must be made much more rapidly to respond to immediate customer and/or market demands. So what if there were technologies available that enabled the Front Office to convert what has been primarily subjective data into objective data? What if the Front Office was able to apply the same rigor to its available data, but in real-time so they could make business decisions?
Cargill Meat Solutions implemented SignalDemand’s solutions (which use historical pricing, USDA market activity, sold positions, inventory and supply constraints) and developed detailed pricing and demand elasticity models for each of the time-horizons in which Cargill Meat Solutions sells its products: spot, mid-, and long-term. Whereas historically this information was scattered through a series of applications and spreadsheets which would need to be manually reviewed, SignalDemand pulls this complex data set together, running it through their models, translating complexity into simple answers — what is the right price, for this product, in this time frame, for this customer? As stated by Bill Chandler, Beef Pricing Manager, Cargill Beef, “It’s given us an unbiased tool as we operate in a very emotional environment to be able to make a good decision.”
The Inexorable Transformation of the Front Offce
With SignalDemand and Cargill Meat Solutions as a prima facie example we now have empirical evidence that demonstrates Revenue Performance Management solutions are beginning to enter the Front Office and make a significant positive financial impact.
While still early, I believe that the compelling economics of RPM solutions such as SignalDemand, Marketo, Cloud9 Analytics, and others will dramatically change the way in which companies manage their Front Office.