“It is essential to have good tools, but it is also essential that the tools should be used in the right way” – Wallace Wattles
If you have been following our “Why Revenue Management Teams Fail” series, you already know how the Knowledge Gap and Process Gap can prevent Revenue Management initiatives from succeeding. This week’s article wraps up the series with the third and final Revenue Management gap – overreliance on tools.
I deal with Revenue Management and Analytics teams regularly. With the advent of these disciplines, there are numerous software tools available for organizations to adopt to drive results. Yet, when I see the output these tools bring, I often find they do not deliver the results required. Even worse, organizations expect these solutions to solve all their problems, which rarely happens. Given the high cost of these software solutions, organizations are unknowingly pouring money (sometimes in the millions) to create a gap within their organization by being overly reliant on tools.
If you are considering bringing on a new solution for your team, think about the following three points to help determine which tool is best for your organization.
1. Organizational Fit
One of the most important things to ensure when choosing your solution is that it fits within the capabilities of the end-user. For example, a client once gave me the analogy of buying a Ferrari and driving it up to a group of cavemen and throwing them the keys and expecting them to drive the car. Sure, the solution is fancy, fast, and expensive. Yet, to the cavemen, it was useless since they did not know how to drive.
Similarly, many organizations tend to over-scope or complicate solutions by choosing the one with the fanciest bells and whistles, even if they are useless to the end-user. Although they are nice to have, if the people and processes are not in place to capitalize on all the features, frustration ensues with little realization in value.
When comparing different tools, it is important to take inventory of the end-user (your team) and match the tool with their strengths and weaknesses. I often advocate for a Crawl-Walk-Run mentality where organizations take progressive steps when exploring a suitable solution which involves phasing in the solution over time with the ability to manage change to the internal process.
2. The Black Box
What is something you have always wanted the answer to? For me, I have always wanted to learn the recipe for KFC’s fried chicken (it’s finger-licking good). When I say that a solution should not be a black box, I do not mean that organizations should divulge their secret sauce, but rather that they should ensure the end-users understand the product they are getting. Time and time again, I see clients get caught up in the marketing of analytical solutions. AI, Machine Learning, Deep Learning, are all buzzwords the marketing team adds to make their solution appear more advanced than they really are. The AI or Machine Learning tool runs an algorithm? So does every other tool. What I suggest is to ask providers deeper questions – What algorithm? What model are they using? How does the model work? These questions help you understand what differentiates one tool from the other, so you do not make the wrong choice. I am a big believer in absolute transparency.
For example, in my many engagements, clients often ask for the source code to replicate our solutions or to try and learn how to code themselves. This rarely works out. Why? Because the secret sauce is not about the ingredients per se but rather how to mix the ingredients to create an ideal outcome. Returning to the coding example, in situations where I do give clients the source code to our solutions, they do not know what to do with it and often will face many technical difficulties along the way. Further, their inability to troubleshoot the problems means they cannot fully implement our solution. All this to say, hold your providers accountable. Ask for transparency. If they push back, take that as a red flag and go your separate ways.
3. Go Beyond Tools
Building on the previous two points, the final consideration is to look beyond a software tool / solution. Many organizations rely on software outputs to turn around business results but that is not a replacement for a process. For example, if a trade promotion optimization engine recommends switching promotional types to decrease trade spend by 1% to drive incremental ROI, that is a great insight. But that is all it is, an insight. Without a clear list of actionable steps that management can give to the sales team to guide them in changing their promotional plans, the insight is entirely useless. Even more importantly, the insight needs to create accountability within the team so that when the recommendations are implemented, you realize results. To ensure a successful implementation and result, remember to go beyond the tools.
There is a lot to evaluate when adding new solutions to your organization, but this is right in our wheelhouse – helping organizations establish successful Revenue Management solutions is what RML was designed to do. Reach out to speak to a pricing expert today.
ABOUT THE AUTHOR Michael Stanisz is a Partner at Revenue Management Labs. Revenue Management Labs help companies develop and execute practical solutions to maximize long-term revenue and profitability. Connect with Michael at mstanisz@revenueml.com
