Corporate leaders struggle with any long-term growth formula because so many growth plans are based on guesses, forecasts, and “bets” on which growth investments will work. Growth plans tend towards these uncertainties because managers rarely agree on three fundamental things: the most essential questions about their growth strategy, the true economic rationale for evaluating strategic growth investment, and the fundamental “math of growth”.

This is an area where advanced analytics and simulation tools can create a lot of value. Analytics give managers the horsepower, processing power and facts they need to better assess the tradeoffs between conflicting corporate agendas and perspectives.  Simulations make it easier to agree upon and align all aspects of the go-to-market model – from sales force strategy to market segmentation to product portfolio, go-to-market, and sales incentive strategy.

Growth strategy is at its core the strategic allocation of business resources to realize the greatest revenues, profits from the market. While there is no one perfect growth plan for everyone, there is a balance that is probably best for your specific company. A common understanding of both the assumptions and expectations of the plan is required on some level, or else execution will suffer.

It’s important to remember that defining, sizing, balancing, and optimization of growth resource allocation depends on a number of interrelated factors. We have been using the SABRE strategy simulation at over 70 top MBA programs to teach growth strategy. These factors are always in conflict. Cost vs. customer service. Sales capacity vs. coverage. Seller balance and fairness vs. revenue maximization. Seller satisfaction vs. short term revenue growth. Sales rep location, skill and expertise vs. market need. This leads to trade-off decisions.  There is no right answer. Each organization has its own priorities, methods, or “algorithms” for balancing these tradeoffs to arrive at territory definition and quota assignments that create the most value for the enterprise – in terms of short- and long-term growth, profitability, and firm value.”

To be more specific, Academic research tells us that there are seven interrelated decision factors that inform the development of growth strategies and plans. These factors include the selling channel designs and go-to-market strategies that every selling system runs on, all of which vary according to the type of information they contain – such as qualitative, quantitative, objective, or subjective data inputs. Selling channel designs and go-to-market strategies also vary based on how they are derived. For example, some organizations use a top-down approach to divide markets into segments and rep assignments. Others use a bottom-up approach that factors in more local market input and the unique capabilities and skills of individual sellers.  The best try to use both to get the most accurate plans in place.

THE INTERRELATED DECISION FACTORS THAT INFORM GROWTH SYSTEM PERFORMANCE

Given this interrelationship between go-to-market variables, it’s important to align all of the components of the go-to-market strategy. They must work in concert with the prescribed territory boundaries and sales quota assignments that generate revenue and yield from resources. Multiple strategic and tactical objectives are in tension and require active balancing. Coordination amongst the key stakeholders in other functions will ensure your territory and quota plan aligns with relevant strategies, such as channel strategy, product portfolio strategy, market segmentation and incentives.

At a high level, business leaders must balance four fundamental tradeoffs when optimizing the growth formula for their company.

  • The tradeoff between high levels of control over the sales force and market coverage. Too much control may limit sales freedom and lead to missed opportunities. Too little control can lead to undisciplined selling, overlaps and disputes. 
  • The tradeoff between cost and the customer experience. Too much focus on optimizing cost can hurt the lifetime value and quality of important client relationships. Too little focus on costs can lead to waste and margin erosion.
  • The tradeoffs between maximizing opportunity and the retention of your sales force. Overly aggressive goals can be unrealistic and lead to stress and attrition on the sales team. On the other hand, relaxing growth goals can leave value and revenues on the table and reduce your competitiveness and productivity.
  • As organizations move to multi-channel, digital and virtual selling models – they need to re-balance selling team activities, roles, and priorities. For example, engaging customers through direct and digital channels requires a much different type, mix and sequence of customer engagement and different customer treatment types. The productivity, workload and capacity  of  virtual sales reps will be different from traditional field sellers or key account managers. Modern engagement models need to factor in the level of digital engagement, reductions in sales travel due to remote selling. You must also factor in the increased speed and frequency of response that digitally enabled customers have come to expect when you establish activity-based productivity measures.

To fully realize the growth potential of new territory designs, interaction patterns, and customer priorities most organizations need to reengineer their selling architecture. This means adjusting territories, incentives, engagement models, roles, and customer engagement cadences to generate higher returns from your revenue teams.

The problem is that most organizations still use desktop productivity tools like spreadsheets to do these tasks. They are not up to the task of planning a complex, modern selling system. Spreadsheet based planning becomes overwhelmed with the volume of variables. Nor can the adapt to customer, competitive and product portfolio changes fast enough to ensure your teams are focused on the right actions and opportunities.  

Advanced analytic algorithms, models and simulators can help assess different scenarios and inform better optimization and resource allocation decisions.

For example, using simulation tools – like SABRE (The Strategic Allocation of Business Resources – provides your growth leadership and revenue teams a faster and more collaborative approach to generating territory, product launch, account-based marketing and business unit growth plans. This unique simulation-based approach has six benefits compared to top-down strategy development:

  1. It compresses time to test go-to-market strategies and scenarios seven years out into the future
  2. It can manage millions of scenarios and possible resource allocations to find the best combination to maximize growth
  3. Balance sales force emphasis, calling priorities, customer targets and treatment types to generate the greatest profit and growth contribution and ROI, and quota attainability
  4. Combine bottom-up local market knowledge and performance insights with top-down focus on realizing the greatest profit, revenue and opportunity share
  5. Pressure test and adapt plans to deal with rapidly changing and different competitive, customer and market scenarios
  6. Accelerate the time between strategy development, tactical planning, buy-in, communication and implementation by revenue teams
CAM TIPPING AND PROFESSOR DAVID REIBSTEIN OF WHARTON DISCUSS HOW MANAGEMENT TEAMS ARE USING SABRE BUSINESS SIMULATION TOOLS TO COLLABORATIVELY AND OPTIMALLY ALLOCATE STRATEGIC GROWTH ASSETS AND RESOURCES TO MAXIMIZE PROFITABLE GROWTH

Analytics offer more  potential to get your growth strategy and allocation decisions right. There are several specific areas where advanced analytics, models and algorithms can accelerate your ability to evaluate different market scenarios and resource allocations. They will help you evaluate many different scenarios faster, as well as allow you to manage many more variables in reconfiguring selling architecture. They can also support you in  optimally matching selling resources with specific market opportunities.  Models can speed up the development and evaluation of a wide variety of trade-off decisions throughout the planning and optimization process, including but not limited to:

  • Sales resource allocation: Optimizing the incremental revenues associated with incremental staffing in a market. Optimizing in this way involves experimentation with different levels and mixes of staffing in different models based on assumptions about sales response function, rep productivity, the marginal cost of incremental sales, and demand elasticity.
  • Sales force emphasis: Optimizing the incremental profit and revenue contribution vs. level of effort, mix of calling and products sold. There are thousands of rep, customer, and personal combinations to consider. Still, selling performance, resource requirements and margins can change dramatically based on these variables. So, exploring many options makes sense if it can be done quickly and affordably.
  • Optimizing territory assignments: Optimizing sales potential vs. the mix of customers and accounts in a given territory can positively  impact sales productivity, total profits and revenue growth and risk.  Planners can experiment with a variety of different combinations to achieve the optimal balance for their organizations. Advanced models can process and optimize territories to balance a variety of critical variables. Some of the most important ones to consider are: Making sure quotas are equal vs. equitable. Balancing carrots (incentives and lifts) and sticks (gates and penalties) to motivate sellers. Emphasizing selling new as opposed to existing products to maximize margins and customer lifetime value. Balancing the time spent with new and existing clients to optimize top line growth and cost to sell. The degree you use activity and behavior as opposed  outcome-based metrics to motivate the right decision-making and effort of sellers.
  • Breaking down baseline revenues and revenue forecasts by product, channel, industry, and geographic mixes.  Understanding how changes in market coverage will impact market share, revenue attainment and cost to sell.
  • Optimizing top-down opportunity allocation. Top-down quota planning breaks down the total revenue opportunity of a company into smaller units that can be assigned to individual sales reps or teams. There are a variety of ways a business can break down that opportunity based on cost to sell, sales force size, product emphasis, staffing levels, and sales force focus.

You can learn more about using these tools by reading our new book, Revenue Operations: A New Way To Align Sales And Marketing, Monetize Data, And Ignite Growth. Our team can provide you background, instructions and SABRE simulation-based planning tools to help you lead a simulation-based planning process with your leadership and operations team.

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