Covid, shaking supply chain, Russia invading Ukraine, shaking supply chain, inflation, shaking supply chain, energy crisis, shaking supply chain, government regulations, shaking supply chain, super-dynamic competitive market, shaking supply chain, thinner margins, cost cuttings, lay-offs, shaking supply chain.
This was daily bread in 2021–2022 for a major part of retail chain managers. For some this was the last straw before getting a new pricing tool.
More than 200 retail CEOs, CCOs, Pricing Directors, Pricing Managers/Analysts, and Category Managers/Buyers have talked to us in 2022 to improve their pricing capabilities and to overcome the obstacles above. Roughly half of them have experienced some pricing tool implementation in their career. 8/10 have been experiencing serious issues that led to postponing or even canceling their projects. In other words – investment losses, management autonomy and reputation risk, time, and opportunity losses. As this is a report, not a book, we will go straight to the point that has been underestimated and has caused such serious issues.
1. My middle-management executed the change poorly – 47%
You as a top manager think that your reports have the same perspectives, intentions, and motives like you – not true!
- Middle management does the hard work around pricing, and they need you to see it.
- This is extremely prone to blind alleys. They consider success if they carry the pricing burden halfway further compared to their predecessor. But how about if this is a blind alley?
- Top managers tend to do things in scale, they know the current pricing status quo might be risky and not be the best one, and different pricing approaches could have moved the company a gear or two up. Middle managers tend to incrementally improve the current status quo. It‘s 100 % valid for pricing!
- Majority of middle managers are not willing to draw back from the blind alley, 2 reasons:
- They are not ready to abandon their last 5 years of work on their pricing machinery – btw. have you ever asked who else in the company understands their pricing machinery? Nobody? To all responsible top managers, this must simply sound too risky.
- Drawing back, they would basically admit to you that for the last 5 years they have been on a wrong path, while a couple of times have been convincing you it’s the right one and asking you for your time and money.
- When it comes to discussion around a new pricing tool, it‘s more beneficial for them to protect their current path. Typically, if they talk about a pricing tool, they tend to shrink the conversation to how they can move 5 meters ahead and if any tool pays off in such a case, while not open to hearing they should move 5 kilometers back first, and then 10 kilometers forward in 6 months.
- Middle managers tend to take the hardest and shortest roads. On those they can show you that they work hard.
Middle managers tend to take the hardest and shortest roads. Only on those they can show you that they work hard.
- Retail chains without dedicated pricing teams are more vulnerable. Pricing tool adoption requires change management, and change management requires dedicated people with adequate buy-in. If you do not have a dedicated pricing person, hire one, nobody can do that well as a side job!
2. We selected a 15 year old pricing tool – 26%
You have been advised to select a 15 year old tool to run automated data and Machine-Learning analytics of millions of transactions and thousands of SKUs. These capabilities have barely been 5 years on the retail tech market. Something is wrong here, correct?
- 15 years ago, Machine-Learning wasn’t available in retail tech. Pricing tools established back then logically couldn’t have this capability on the stack.
- In the last 5 years top managers consider Machine-Learning as a must have for automated data analytics for excellent decision making, pricing included.
- Today, tools from 15 years ago don‘t have other options than “somehow“ add this capability to their stack. It doesn’t work, as well as adding an electric engine in the front section of a diesel car, and the battery on the roof cannot be called an electric vehicle. Imagine how risky it would be for the stability of the car having a battery on the roof. A new platform needs to be built from scratch in the car industry. Same with Pricing SaaS and Machine-Learning capability.
- While the “older“ tools are undergoing total replatforming currently, there have been multiple Machine-Learning and native pricing tools born in the last 5 years or so.
3. We were not ready to streamline our pricing processes – 14%
Your top manager insists on referencing prices A to prices B as this was the routine over the last 10 years. Is he/she helping you undergo changes, or just protecting himself/herself from making any?
- Yes, linked to point 1.
- Example: Item price referencing = an issue!
- Middle managers tend to connect the price of one SKUs to the price of another SKUs. The reason is obvious – at the beginning it seems to be time efficient!
- Same with store formats – hypermarkets 3 % cheaper than supermarkets (all assortments!).
- Same with regions – countryside 3 % cheaper to suburbs which are 2 % cheaper to cities which is 1 % cheaper to the capital.
- This ends up with prices of one operational part being totally linked to another operational part. All top managers know that this doesn’t reflect the reality of different regions, formats, channels, customers, categories, or SKUs, and it’s only a simplification made by middle management. We’ve never seen anyone who would be able to combine this flexibly with competitive intelligence and margins rules. For example: “Hypermarkets are 3 % cheaper than supermarkets covering total assortment, and at maximum 5 % below, respectively above competition, and margin above 22 %. This is uncontrollable simply because competitive and margin rules only make sense in relation to specific assortment. For 10 departments, 40 categories, 300 subcategories, 1 simple rule becomes 10, 40 respectively 3.000 rules to be manually managed, that have 30, 120, 9.000 more parameters compared to the original one. Therefore most of the middle managers who use 100 % price reference ability to make their life easier at the expense of margins, customer loyalty, and position in the market end up with typically a simple rule: Hypermarkets are 3 % cheaper than supermarkets covering total assortment.“
- Expectations in contrast occur – full pricing automation vs. control example.
- Tony: “We can simulate and set our pricing strategy in the tool to further calculate our optimal prices for that strategy within the limits set by us.”
- Laura: “Can those limits be automatically optimized, and best strategies automatically chosen too?”
- Tony: “I wouldn’t recommend it; we could easily face the risk of losing control.”
- Laura: 🤔
- Sometimes it takes a village for Tony and Laura to align their thinking and streamline it alongside processes and responsibilities.
4. We required IT customizations for the new pricing tool – 7%
Tailored IT development is fun, cool, easy, relatively affordable, a good way of solving a problem – not at all!
- A usable pricing tool in any retail company will never ever be created through collecting all the ideas from the Commercial department, BI/Data department, Marketing department, and Operations declaring those as the definition for RFP/RFI.
- How much are your middle managers asking Pricing SaaS vendors what they have learned on tens and hundreds of tool implementations?
- Pricing SaaS vendors can guarantee quality, time, costs for the solutions as is. With requirements that need IT development, your middle managers are putting all these under risk, and take money from your wallet.
- If top managers want to mitigate this, they should invest time and energy to evaluate the best fitting tool to their needs. If it fits 80 %, it’s good enough, typically 15 % is drawing back from a blind alley, and the remaining 5 % can be subject to IT customizations. Top managers should be present when the new pricing tool is being selected to make sure they will not pay their margins for middle managers‘ comfort.
5. Others – 6%
- Typically, underestimation of: Internal resources, data quality, corporate/group buy-in, internal relations.