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Price Management Solutions – A Truck, Tree and Prevention View

January 23rd, 2019 (Updated 06/20/2023) | 8 min. read

By Gabriel Smith

Key Takeaways:

  • One issue that price management companies face is “The Truck”; having only one person who takes care of all or most of the pricing process
  • Another issue that companies face is the “The Tree”; not having a system that can analyze and predict vulnerabilities in your pricing process
  • Preventing these obstacles requires improving on the following factors: people, processes and systems

At Pricefx, we speak to industry-leading companies every day about their pricing and quoting processes, and their opportunities to improve them. There are two recurring themes in these discussions, which I will call “The Truck” and “The Tree.” The last section of this article, “The Prevention”, will take you through the different ways in which you can overcome the obstacles these issues present.

The Truck – An Obstacle to Price Management Solutions

First, the Truck. Recently, we kicked off a proof of concept for a distribution customer and walked through an in-depth review of their current process for pricing. The process was quite sophisticated, but built using Excel and Access, which caused challenges in terms of scale, speed and the level of segmentation and analysis they could employ. There is one pricing manager at the organization who built most of this process and we got the sense that he was the only one who really understood the entire model in both theory and practice. It led me to say to the Pricing VP during a break, “Wow, you have quite a Truck Factor with this particular person,” meaning if the pricing manager was crossing the street and got hit by a truck, they would be in trouble. His reply was classic, “Yeah, I have truck anxiety. I don’t want him crossing streets!”

Hidden Bugs and Retirement Heaven

Additionally, having one person responsible for your pricing model could lead to weaknesses that you are completely unaware of – according to studies, as many as 3.2 bugs per line of code or formula in Excel/VBA. In this project, we corrected a bug in their calculations which led to significant uptick in profitability.

When I was at Cisco Systems, there was a famous Software Engineer that developed the software used to do auto-testing on most of the manufacturing lines at Cisco and our contract manufacturers. It had a 99.9+% uptime, which was needed because if it went down, manufacturing would literally stop. He had retired to Hawaii but had a special arrangement that included a T1 line, travel restrictions and lots of money, of course.

It amazes me how many multibillion-dollar companies in the world have processes built like this that only one person understands. If that person leaves for another position, wins the lottery or is otherwise suddenly gone, the business could literally halt.

Food for Thought: Do you have a “truck factor” employee on your team? How can you mitigate this risk?

The Tree – Predictive Pricing Analysis and Optimization

“If a tree falls in the woods…” you know the rest. How does this apply to price management and optimization? Well, allow me to explain. Imagine a forest full of trees, each tree representing one of your customers. You supply these trees with something they value, perhaps something they cannot do without, such as carbon dioxide, sunlight or water, or perhaps something that allows them to utilize these necessities more effectively. This keeps the trees healthy and vibrant, allowing them to thrive in a competitive ecosystem where there are numerous threats to their existence (such as other trees taking sunlight, pests and environmental factors). You are as dependent on their survival as they are on yours, so it’s a symbiotic relationship.

Now, imagine, suddenly one out of the thousands of trees in your proverbial forest falls. Did you hear it? Were you listening for it? That is a question rear-facing analytics can answer, should you have the right data and ability to examine it. But, in reality, the more important question is this: “What were the warning signs that I could have seen to prevent it?” Now, we are talking about the basis for predictive analytics, with which you can see and alert your organization to an impending problem before it is too late to adjust.

Price Optimization, Management and the Fourth Industrial Revolution

This is the basis for the Fourth Industrial Revolution. It sounds like a leap, but bear with me for a minute. Like with other industrial revolutions before our time, predictive analysis leverages powers like artificial intelligence and machine learning that few can grasp. And like previous industrial revolutions (the steam engine, rise of science and digital technology), the byproducts of this revolution are becoming increasingly democratized by big data, sensors, affordable memory, computing power and the workforce skills required for synergy.

Society has only begun to harness this power and been affected by its long-ranging socioeconomic impacts. But in certain areas, we are already able to leverage this technology to radically improve upon the status quo.

One such area is Price Optimization and Management, where you can apply data science, machine learning and management insights to drastically increase the speed and effectiveness that come with using intelligence. You cannot just see why something happened, but predict what will happen and take corrective action before the tree has fallen. For more information on how, please see my upcoming webinar on “AI and Machine Learning powered Price Optimization: What you need to know.”

Predictive technology will transform not just pricing, but society as a whole. According to Gartner, 20% of workers will require AI to assist them with their jobs, but the good news is that more jobs will be created than lost. Regions and companies that prepare for the change by making appropriate investments in education, technology and people will benefit the most.

So, How Can You Prevent the Truck and the Tree?

As with most issues in the corporate world, there are three factors involved: People, Processes and Systems. They all work together to enable you and me to resolve problems. Let’s discuss both the Truck and the Tree in their contexts.

The Truck Factor – Building Redundancy in Your Price Management Processes

  • People: When it comes to people, redundancy does not sound good, and, of course, there are going to be specialists in any organization with knowledge that no one else possesses. We all know those “go-to” people in an organization that seem to know everything and are, thus, indispensable. I am proposing that when it comes to critical business processes, there be some redundancy. These are the processes that can halt business should our “go-to” hero win the lottery or abscond to a foreign shore. Identify critical processes and start onboarding or hiring the right employees to create redundancies.
  • Process: There are two ways to create processes that will avoid the truck. The first is through documentation and good mentoring on critical business processes. Another is by putting these processes into a system and automating as much of it as possible, which brings me to my next points.
  • Systems: You probably guessed that I am a pricing software guy, so I will focus on the systems aspect. As I mentioned above, the system is an enabler for people and processes. By itself, the system will not solve all your problems. However, in conjunction with people that know the processes they want to enable, a properly implemented and integrated system will enable step-function improvements in many processes that simply cannot be achieved without it. When implemented, we have seen a 2-4% return on sales on numerous occasion, further proven by hundreds of case studies by Deloitte, Gartner and AMR.

The Tree Factor – Predictive Analysis in Pricing

  • People: The employees in your organization need to keep their eyes and ears open. In SaaS and other subscription companies, this is the role of “Customer Success,” to monitor what is going on and to pre-empt issues that may arise. Companies like Pricefx use tools to monitor customer health metrics.
  • Process: There must be processes in place that measure factors affecting your bottom line and adjust if something is detected that requires action. Measuring is the first step, but you also need to empower the people doing the measuring to act as they see fit, without unneeded bureaucracy. This is the essence of being customer-centric: listening to what your customers are saying, but also trying to sense what they are thinking by analyzing their actions. Are they ordering more from you or less? Are they buying more categories or less? What is your wallet-share and how is that changing over time?
  • Systems: As you can imagine, the answers to the questions above and others are vastly easier to determine with software. For SaaS companies, we have the luxury of being able to see how our solutions are used in real-time, which we use as a key indicator of customer health alongside several others. On the other hand, more traditional businesses depend on purchasing behavior, customer service calls, timeliness of payments and Net Promoter Score. There is contention on the effectiveness of Net Promoter Score, but that is for another post.

A lot of organizations can avoid “The Truck” and “The Tree” by building redundancies and introducing predictive analysis into their processes, people and systems.

I hope you enjoyed this post, please like and share. If there are other topics you would like to see me post going forward, please let me know.

Gabriel Smith

VP Global Account Strategy & Chief Evangelist , Pricefx

Gabriel Smith is the VP Global Account Strategy & Chief Evangelist at Pricefx. He has more than 20 years experience in CPQ, enterprise software, SaaS, with particular expertise in lead to order, pricing, incentives, product management and solution sales. He has worked with market leading companies like 3M, Anda, Avery Dennison, Cisco, CertainTeed, Cox, IBM, Seagate, and Sonoco to improve their profit and processes through digital transformation of their pricing and CPQ processes and using AI to optimize pricing. He is a father of 2, attended UC Berkeley and lives in San Francisco.

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