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10. HOW to Align for Strategy Execution: Strategy Decision Model. With the Religence Framework probabilistic strategy decision model we quantify the current situation and consider alternatives. By modeling alternative strategies to evaluate likely profitability, strategies and their supporting tactical plans can be adjusted until profit is more assured—in advance of investment in execution. Five Steps to Align for Success in Strategy Execution. See our Next-Generation: Profitability Segmentation paper for a discussion of them or learn more about our profit matrix, a preferred method of ours in planning. Not only is it a method to sort out “what is” happening with customer and product total contribution to profit currently, but the exercise stimulates ideas for “what could be.” 2. Drill down to the channel/product group combinations within the customer segments with profit improvement potential. This is the smallest unit for effective action. It is at this level that relationships are made and the people who make them are managed. Please see our Next-Generation: Strategy Execution paper for how to align teams on the frontline with customers at this level with executives and the company’s directional strategy and goals, using an action learning team approach. 3. Evaluate how well you are aligned for success in strategy execution and value creation with this channel/product group combination. Our Align for Success Factor self-diagnosis method is a reality check management teams use to see how prepared they are to deal with customers and the marketplace. The tool is one of several of our models to quantify “what is” and help stimulate ideas for “what could be” done differently. The factor helps quantify the market opportunity and the elements of customer value—brand value, product value, and relationship value, using nearly 100 external and internal considerations that success depends on. 4. Model the current or status quo customer relationship strategy as well as alternatives. With each strategy, an action learning team outlines at a high level the tactics and the process used to move customers through Acquisition, Closing, and Retention stages in the customer lifecycle as a continuum. They estimate conversion rates and variable cost-per-contact for each stage. Other key metrics are retention rates, referral rates and Customer Lifetime Value (CLV) for profit. These are the key metrics in planning.
The strategy discussion can get heated as passions rise in defense of different approaches. The model is the referee. For example with a software company, which had grown organically and wanted to grow to be acquired, the fight was between the CEO and the sales manager over which strategy would be best to grow revenue the fastest, on a limited budget. Close to half of the software company’s prospects had come from customer referrals. The other half had come from the Web and traditional marketing efforts. Prospects were converted to new sales either by an automated closing on the Web or by personal touch. Upgrades kept customers repurchasing. Here was the process they were using, mirrored in the strategy decision model:
Below is the tactical plan overview they were using for their current strategy or status quo. The same format was used for the tactical plan required to execute each additional strategy being considered. In execution, this format for the chosen strategy will be carried forward into a coherent tracking system, in a way that can be monitored and related back to individual elements of the plan.
The CEO and sales manager of the software company agreed that they should spend more on infrastructure tactics like trade ads, online PR, and evangelizing to build the value of their brand and more on direct tactics like ad words and ad links for sales leads. It was what to do with the money they had left that they disagreed about.
The CEO wanted to focus on direct marketing for acquisition and get more customers from the people reading his industry’s leading publication. The sales manager thought they should put more effort into building their user community and promoting to their customer base to leverage the relationships they already had. She had a point. They had a strong referral base. Which one was right? This was a fight that only a strategy decision model could love. The model made the complex sales and marketing process simple enough for the software company planners to easily estimate costs, volumes and rates. In this rendition of our strategy decision model, the model is executed in Lumina Decision Systems’ tool Analytica, a sophisticated modeling tool with probabilistic simulations integral to its design.
For example, the software company planners estimated conversion rates of suspects—coming in from Web ads, Web traffic and other non-referral sources—to prospects for each strategy. The 50% percentile is similar to point estimates commonly done, but adding in estimates at the 10% and 90% percentiles allowed them to express their level of uncertainty in their estimate—in other words, how low or how high might it be.
The software company’s goal was to increase revenue to be a more attractive candidate for acquisition. To resolve the fight over where to put their limited budget, they developed two alternative strategies. Strategy A, the middle bar, involved doing more retention to leverage customers for more referrals, and Strategy B, the far right bar, involved spending more on acquisition with traditional direct marketing. They then used the strategy decision model to find out which strategy is more likely to make money and help them reach their revenue goals.
Fixed and variable costs were pretty much the same between Strategy A and Strategy B, by design to give a fair ROI test to the two strategies in the model. But it was the variable cost that could hurt them in execution, given the large share of the budget it represented. They’ll know if their forecast is right when data begins to flow from the operational CRI tracking system upon execution. You can be sure they’ll be paying attention and making real-time adjustments as needed. They are expecting to be somewhat surprised. They haven’t been able to track variable costs before.
Strategy A, the middle bar in each set, is the clear choice for increasing revenue over the three years.
Strategy A is also the clear choice in terms of NPV (net present value) profit and the probability that the profit will be achieved. Analytica’s Monte Carlo analysis capability gives a cumulative probability distribution. Strategy A on the far right beats out Status Quo on the far left and Strategy B in the middle at the mid point and at the 100 Percentile. They were not totally surprised to see the dangers of maintaining status quo and staying with their current strategy. It was not going to help them grow significantly any time soon and they could lose ground. 5. Choose the best strategy. Without a model to evaluate all the factors and all the tactics, all too often a strategy decision is made without enough information. Or without a complete picture on the ROI. Or without knowing which metrics are the drivers. (In the case of the software company the number of referrals per customer was a driver. If that number dropped, the strategy had to change. We expect the CEO took some comfort in that, having lost the original argument.) The strategy decision model discipline leads to better decisions. You have a better idea of
To operationalize it, the action learning team will need to define, quantify, and value the possible interactions for each tactic. Please see our Next-Generation: Strategy Execution paper for an introduction on to how to do this or see our CEO’s new book Customer Relationship Intelligence: A Breakthrough Way to Measure and Manages Sales and Marketing, Chapter Seven. For more about customer relationship strategy and tactics, please see Chapters Five and Six in our CEO’s new book. Or invite us in for a workshop on strategy execution or attend a webinar. |
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