Platt Perspective on Business and Technology

Moving towards dynamic performance based business models 5: scaling up and expanding within sound performance-based constraints

Posted in startups by Timothy Platt on March 25, 2013

This is my fifth posting to a series that seeks to outline a basic approach for developing and fleshing out a best-fit business model for a specific business and its context, so as to gain and sustain operational and strategic effectiveness and competitive strength for it (see Startups and Early Stage Businesses, postings 123 and loosely following.)

• I have been developing this series as a performance-based and operationally oriented approach to business models, where many if not most business models are either goals and strategy centered, or centered on specific resource bases or technologies that would be employed, deployed or built upon (e.g. web 2.0 business models – see this relevant posting as a general reference on that.)
• I have also been posting an extensive and still ongoing series on business expansion and scalability per se (see Startups and Early Stage Businesses, postings 96 and scattered following for that, at 25 installments as of this writing.)
• This, posting can be seen as a point of intersection between these two basically separate discussions, and my goal for this is to consider how selection of appropriate metrics can improve scalability, and how metrics themselves evolve to keep pace with the business expansion process.

Basically, that means this posting is about scaling up a performance based business model per se to keep it relevant and connected. And I begin this discussion with two fundamental questions:

1. Precisely what in the business operationally, has to be scalable for the business to expand and grow?
2. And of that, what can simply be scaled up linearly (scaled up through replication and growth along an established pattern), and what would have to be scaled up in new ways, breaking out of established and already vetted and validated patterns? This later alternative is termed nonlinear scalability.

Note that I did not explicitly include the issues of prioritization in those questions. True, some performance metrics – some numerically scorable business parameters, start out as carrying higher or lower priority as to their need for ease of scalability, and for following a linear scalability pattern. At least an initial presumption of higher importance would be expected, for example, where specific metrics are used to track performance for operational processes that create or maintain a business’ sources of value that distinguish it from its competition. But as a general rule, any business parameter that is not smoothly, easily scalable, that was not developed to make it so, becomes a key priority if that business grows, and it is in effect left behind in that process. And when a particular measurable, metrically analyzable parameter is proving itself to be problematical for clearly determining business position going into a proposed expansion, it may have already been pushed through prior growth to a point where linear expansion of its use is not working anymore for it.

• My point is that the issues and challenges of prioritization for updating and expanding performance metrics are not as much properties of those metrics or of the specific process and function areas of the business and its operations that they track,
• as much as they are of how successfully and effectively growth has been strategically planned out – with any operational or performance measurement gaps created leading to and in fact defining points of redesign priority for moving forward.

So answering both of the questions posed above has to begin with knowing what has to be scalable, and knowing its status going into any given proposed strategically planned expansion effort. Are the business defining metrics in place still linearly scalable or has the business already pushed past the limits for effective linear scalability for them – creating need for fundamental changes in the business and its underlying performance model if it is to scale up further from where it is now? And this has to be addressed on an ongoing basis as a matter of ongoing expansion assessment, and as part of both ongoing operational and strategic reviews to keep any significant business expansion on-track. Remember in this – operational processes have to be scalable for a business to smoothly and effectively scale up; performance metrics in place have to track that and with consistent reliability that means their scaling up in synch with what they performance track. So performance measures are the analyzable surrogates for business performance itself.

• The simplest expansion examples that I know of all involve replicating a proven model store or restaurant or other chain outlet into new sites, with very tight quality control to keep everything following the established pattern.
• One-off expansion generally begins with nonlinear scalability issues and with the greater costs and risks that this entails, where as noted in my scalability series (cited above) risk here has to be calculated as a potential cost based on likelihood of a given event happening as multiplied by the anticipated costs if it does.

I am going to turn in my next series installment to consider the organizationally complex business where through acquisitions or other means, separate divisions are operationally run separately and with their own processes and even much of their own strategy. I have written several times about innovation centers in this blog (see for example my series: Keeping Innovation Fresh, at Business Strategy and Operations – 2, postings 241 and scattered following) and I will focus on that business approach as a source of working examples. Meanwhile, you can find this and other related postings at Startups and Early Stage Businesses. You can also find related material at Business Strategy and Operations and at its continuation page: Business Strategy and Operations – 2.

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