Most management teams do not lack business growth options. The harder problem is choosing among them with incomplete information, when each option has a cost, a range of possible outcomes, and effects on the others. As part of developing a client’s Growth Strategy, I build an options model to help them easily understand the effects of every growth option: every option is valued as a range, every number states its basis, and every combination is judged against the company’s break-even or current state.
The model below is a working example. The business is fictional and its figures are invented: a B2B software company with about $4.5 million of recurring revenue, selling supplier onboarding and procurement software to mid-sized manufacturers. The structure is the one used with clients.
The benchmark depends on what the company is seeking. A company that is not yet profitable and is seeking sustainable profitability is judged against break-even: the gross profit it needs to cover its costs. A company that is already profitable and is seeking a new growth curve is judged against its current state, and the question becomes how far each combination lifts gross profit above it, and whether that lift meets the growth target the management team sets. The model offers both objectives. The example company is short of break-even, so it opens on sustainable profitability.
Fourteen options were assessed and five were modelled
A growth plan that carries every reasonable idea dilutes management attention and capital across all of them. The model starts from fourteen candidate options and carries forward the five with the largest effect for a business of this size: raising renewal retention; CRM automation and AI augmentation across sales, marketing, and customer success; a pilot-first then expansion sales motion; an outbound business development team; and an implementation partner program.
Three further options (freemium pricing, new geographic markets, and verticalized product variants) would each reverse a decision the business has already made. They are shown so their effect can be seen, and marked so they are not mistaken for recommendations. The remaining six are listed with the reason each was set aside, two of them because their effect is already counted inside another option. A list of what was not chosen, with reasons, is as useful to a management team as the list of what was.
Ranges show whether a plan survives underperformance
Each option carries a cautious, middle, and strong value. A plan that clears break-even only at the strong setting depends on everything going well; a plan that clears at the middle setting and stays within reach at the cautious setting is more robust. In this example no option set clears break-even in its first year at the cautious setting, at any market stage. In the early majority, only the full set of five clears it at the middle setting. That finding is the starting point for a conversation about sequence and risk, not a reason to stop.
Options interact, so their effects do not simply add
Two options often claim the same gain. The retention program and the customer success automation in the CRM option both reduce lost renewals; choosing both counts that reduction once. Some options also depend on others: the business development team reaches its middle value only with the CRM automation that supplies its routing, sequences, and signals, and counts at its cautious value without it. Counting overlaps once and stating dependencies keeps the combined plan from looking larger than it is.
Related reading: Which Drivers Depend on the Others, and Which can be Invested in Independently?
Capacity converts growth into hiring cost
The onboarding team in this example can deploy and support about $5.2 million of revenue a year. Past that point, each additional $600,000 of revenue needs another onboarding specialist at about $110,000 a year, counted in cost of revenue, or an implementation partner to deploy it at a lower margin. The model shows both and compares them. Hiring tends to earn more on large volumes; partners tend to earn more on small ones, because a business cannot hire a fraction of a specialist. The dashed line on the chart shows the same business with no hiring: gross profit stops rising at capacity.
Retention is worth less in its first year than at its run rate
Raising renewal retention from 75% to 85% keeps about $450,000 a year of a $4.5 million base once the program is in place. In its first year it keeps about $300,000, because renewals fall due across the year and a new program reaches them from about the fourth month. The model counts the first-year figure and shows the run rate beside it. Treating a run-rate figure as a first-year result is one of the more common ways a plan overstates its own return.
Related reading: Love: Retention and Customer Lifetime Value
The market’s stage changes which options pay
Where a category sits on the adoption curve (Rogers, 2003) affects what buyers need and therefore which options work. Early adopters respond to pilots that prove a new approach. The early majority wants references, a complete product, and a partner to implement it (Moore, 2014). The late majority compares on price and integration and tends to stay with a supplier that works. The model scales each option by a stated multiplier for each stage and moves the point beyond which the evidence does not support a higher share.
The effect on the decision is material. At the middle setting, the pilot-first set clears break-even with early adopters while the partner and business development set does not; in the early majority the order reverses; and in the late majority the options that protect existing revenue carry more of the result. The stage is a judgement, set from the category’s adoption among the firms in the market rather than read off the curve, so the model is designed to be tested at each stage.
How the model is used in an engagement
With a client, I set every value from the client’s own records and research: renewal history, pipeline and win rates, capacity per person, and the market sizing. Each value is agreed with the management team before it is used, and each carries a basis line so it can be challenged and corrected. The model does not make the decision. It makes the trade-offs visible enough that the management team can make it with a shared view of cost, range, and risk.
The model draws on the framework in The Six Drivers of Business Growth: products, markets, partnerships, pricing models, business processes, and financing.
Related reading: The Six Drivers That Drive Business Growth
How I can help
Through my Authgnosis consulting practice, I build options models like this one from a client’s own records as part of its Growth Strategy, so the management team can compare each option’s cost, range, and risk before committing to a plan. If you would like to discuss your growth options, reach out to me here.
References
Moore, G. A. (2014). Crossing the chasm (3rd ed.). HarperBusiness.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.