3 Keys to Success with your RM Initiative
Executive Summary
Building, enhancing, or overhauling an analytics program/system is a critical initiative for any organization. Many such initiatives are fraught with delays, technical integration challenges, and adoption issues — all resulting in slower than desired speed to value and lower than expected return on investment (ROI). And in the context of Revenue Management (RM) systems, these challenges are amplified due to the frequency of revenue-related decision making, level of automation required, and direct impact on top and bottom lines.
In our experience working with clients on a variety of RM initiatives from concept and strategy through implementation and ongoing support, the leaders of the most successful RM programs do these 3 things:
1. They know their capabilities and play to their strengths. Leaders of the most successful RM programs either have or attain a true read on their company’s capabilities and gaps…and then they close gaps while playing to their strengths
2. They live by the “no best, only better” rule. Leaders of the most successful RM programs avoid making perfect the enemy of good…instead of “getting to perfect”, they “get to impact” and leverage concepts like Agile to continuously improve their RM program over time
3. They know the key to adoption (and success) is held by their internal champions and stakeholders. At the outset of their initiative, leaders of the most successful RM programs quickly find and invest in their internal champions and business stakeholders
1. Know Your Capabilities & Play to Your Strengths
Whether you are creating an RM program from scratch, enhancing your RM system, or completely transforming your RM capabilities, a true and unbiased assessment of your existing capabilities is needed. Once you have this view, you can play to your strengths.
For the benefit of our clients, we use a Guided Discovery methodology (see graphic at right) which allows organizations to quickly yet comprehensively understand where they are today, which opportunities will have the biggest impact, and what the best path forward looks like.
A top-down revenue/margin leakage analysis kickstarts the Guided Discovery. This helps identify aspects of a business or components of a system that are working below par, as well as gaps in existing capabilities.
2. Live by “No Best, Only Better”
Getting to the perfect analytical result that optimizes to the 99.9th percentile is the holy grail for many a data scientist. Ensuring that an RM system has every piece of functionality possible might be considered best-in-class by process ninjas.
However, this “pursuit of best” requires serious squeeze — many times for little juice — and it always results in spin cycles as teams wait for all stars to align. Even if “best” is achieved, it might be fleeting because the business will inevitably change.
With your ever-evolving business dynamics and inertia, making “good” capabilities “better” over time has a much stronger ROI pursuing perfection before progress.
3. Your Internal Champions are your Key to Adoption (and Success)
Seek out your game changers: The disruptors who are on board with — or at least open to — a change and adopting a new approach and join forces with them early. Provide your champions and business stakeholders with a platform to contribute ideas and even get an audience with your C-Suite or Executive team. Engage with them during the Guided Discovery process, if not before. Understand their pain points and goals. Consider making tradeoffs to accommodate their requests and ideas.
Early wins for your champions and stakeholders will give your initiative early positive momentum, potentially unlocking access to other resources in the organization. Additionally, internal recognition and awards that demonstrate the value of such contributions can go a long way. Once business users begin realizing value from your new RM capabilities, the rest of the organization will follow their lead — many times just from a fear of missing out!
About the Authors: Jeff Anderson is a managing partner and the Chief Growth Officer and Anand Srinivasan is the Chief Scientist and Head of Data Science at Kaizen Analytix.