How a new structure is required to improve strategic planning.
In the Old Testament, God created distinct languages so that the people of the Earth could not talk to each other and build a tower to heaven. The biblical Tower of Babel was never completed because of it.
Today’s retail executives have the opposite problem: every department in their company has its own metrics, its own way of thinking and its own “language”. This makes it difficult for CEOs to make key strategic decisions that will transform retail growth. Retail executives need to embark on a mission to build their own Tower of Babel. The first step is getting everyone to talk the same language.
In most corporate environments today, each department is in its own “silo,” making use of only its own reports and data:
This approach invariably creates blind spots. Each unit has its own data sources, tools, metrics and reports, and they are all perfectly designed for incremental improvement. The lack of smart integration makes it impossible to get to the fundamental knowledge of where to shift the company’s overall resources, time and energy.
But what if all were to talk the same language? What if you had your own Tower of Babel? If retailers were able to easily make decisions across different departments, resources and regions? A common business language allows retailers to move from tracking performance and starting with solutions to a focus on opportunity and finding the right tool for the job. Opportunities start company-wide and then go top-down into resources, departments, and finally into meetings, metrics and reports.
Let’s look at just one example of many. It starts years before my company was called in to consult. This particular retailer kept opening store after store each year because management followed the vision that expansion through store launches was the best strategy for growth. The challenge with the strategy was that they were unknowingly adding very little net revenue. Despite having all the necessary data available, they were blind to the real profitability. Why?
Data didn’t cause the breakdown – not having a common, integrated analytical approach did. All the necessary data was at the executives’ fingertips but broken out into different data siloes within different departments. What was missing was their own Tower of Babel with all of the key information put together into the same language.
Here is what was happening. The real estate department received a projection of the sales for every future store. If the sales projection for each store hit a key threshold where the store’s income statement looked good, it got built. The average new store was projected to do $20 million in sales and $2 million in profit. The finance operations department, located in a different corner of a different floor at head office, knew that when a new store is being built, existing stores in its vicinity need to adjust their sales plans. How did the finance department know? Because local store managers would call head office, screaming that they need a plan adjustment. They know a new store will cannibalize their sales and thus demand a reduction in sales goals for next year. As a result, the finance department built a model for new openings that predicted the sales impact on existing stores and adjusted each store’s sales plan accordingly, in this case by 15%.
15% cannibalization doesn’t sound too bad, does it? However, there is an unintentional lie in this data. The 15% cannibalization isn’t based on the new store’s sales, but the existing stores’ sales, and this innocent switch in denominators blinded the retailer to what is really happening. Each new store impacted three existing stores, with each existing store doing $30 million in volume. Though the new store will do $20 million, an existing store does $30 million. So 15% x 3 stores x $30 million = $13.5 million in cannibalization. Notice how the 15% hides this number? Working in percentages, which is how most retailers think and talk, creates huge issues with changing denominators. But here is the real kicker; the $13.5 million shouldn’t be compared to the existing stores, but to the proportion of the new store’s sales. The real insight is that 68% (13.5/20 = 68%) of the new store’s sales are cannibalized. So when the CEO asks for the cannibalization and was told it was 15%, the true impact and more accurate figure of 68% was lost in translation. You only get to the truth by having the right metric and a common Tower of Babel language which everyone speaks. When I asked the CEO if he would have ever approved a store opening with 68% of its sales coming from existing stores, what do you think he said? Analytics is not easy. The data matters, the analysis matters, and having an integrated approach (a Tower of Babel) matters.
So why were we able to figure this out, while the client was misled? The math seems straight forward. The reason is it actually really isn’t about being smart enough to do math, but having the right process in place. The finance department is working on their task of adjusting existing store sales; it isn’t even on their radar to think about the validity of opening the new store and so they don’t even share their knowledge with the real estate department. And even if finance did tell real estate about the 15% cannibalization, without adjusting it into a common language (i.e. 68% of the new store’s sales instead of the finance language of 15% impact to existing stores) the true insight would be lost.
And it’s not like it’s in the real estate department’s best interest to uncover that the stores they proposed opening are at 68% cannibalization. It is in the interest of the real estate department to open stores, and any knowledge that opening stores cannibalize sales would work against the size of the budget and team. They may not have wanted to be blind on purpose, but why would they aggressively pursue something that is not in their interest? So they focused on opening one store after another.
If finance is working on their job of sales adjustments, and real estate isn’t really in the job of making themselves look bad, then who is looking out for the company? Even if you were an analyst working in operations, merchandising or marketing and you uncovered this issue, who would you share it with? The VP of Marketing isn’t going to pick a fight with real estate on this because it isn’t their battle. There is simply no incentive to integrate insights together into a common language, no structure to do so and nobody in charge.
Later the retailer asked my team to come in and help them improve business performance. We approached the situation with fresh, analytical eyes and put the math together. In other words, we started to work with them to build a Tower of Babel. We looked at new store sales minus cannibalization, and adjusted the profit and loss statement accordingly. It turned out that over 20 of the new stores built in the last three years were losing money. Here is what the real estate department, finance department and CEO saw, and what they should have seen:
|Real Estate View||Finance View||What the CEO needs to see|
|New store does $20M||3 existing stores being impacted||New store does $20M|
|30% gross margin||Each existing store’s sales go down 15%||$13.5M ($30M x 3 stores x 15%) in revenue cannibalized from existing stores|
|Fixed costs of $4M||Sales go down from $30M to $25.5M per store||Actual net sales of $6.5M in new sales|
|30% gross margins|
|Fixed costs of $4M|
|Net Profit: $2M||Net LOSS: $2.05M|
Data was available but spread over two different departments. The result: Nobody knew that by opening a new store, net profit for the whole system goes down $2M for each store opened. The real estate department excels at picking store locations and managing capital projects. But strategic business analytics is not part of this department’s core expertise and putting it there may be a source of conflict since more comprehensive models may directly impact the department itself, including asking real estate to shrink its budgets and teams.
The finance department runs the books and just wants to know what each store’s sales plan is next year and get it into the system. The CEO and CFO may ask for more data, but all of the necessary data was there already, sitting pretty in different silos. The missing piece of the puzzle was somebody tasked with picking the right data and putting it together in the right way.
In Canadian retail, this type of scenario happens every day because nobody is in charge of best-in-class, integrated opportunity analytics across the whole organization. In these old-style organizations, data and analytics are all about tracking, not opportunity. Executives receive bottom-up, “siloed” solutions instead of top-down insights from opportunity to resource allocation. The system fosters a culture of being precisely wrong and not one that leads to accurate decisions. It is full of isolated, incompatible metrics. This is a fundamental challenge that prevents growth in many retail organizations.
In my nearly two decades of working as a retail analyst, I’ve often seen decision-making like the following: “Our margins were 35% last year, so this year the goal is 35.5%. Last year we spent $40 million on marketing, so this year we’ll spend $42 million.”
Why is this normal, and not what the best-in-class retailers do? Typically, departments are asked for their plans first. But it is from identifying opportunities that a conversation begins on which departments align best to that opportunity and need more resources. And, just as importantly, which departments align least to the opportunities and need to rationalize their resources. A process focused on getting to the right questions and finding the right data requires department-agnostic analytics.
Why don’t many Canadian retailers plan this way? It’s because there is no Chief Analytics Officer (CAO) with one integrated view of the business. The CAO role would consolidate all forms of analytics currently spread across the retailer (e.g. consumer insights in marketing, financial analysts in Finance) under one department, to build one common company-wide language so the CEO would have the “one truth” and knowledge to make the most profitable decisions for their business.