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Today’s Business Model: Keeping Up With A Moving Target

Sean Salleh 05 Sep 2013 Modeling methods

Tomorrow, today’s business model will be yesterday’s. Behind that self-evident observation lies an uncomfortable fact. The rate of change of such models has accelerated over the last decades. Success stories like Amazon go through business model after business model in order to remain competitive and expand, leaving many analysts and observers confounded. When things move this fast, enterprises need a solution that is also flexible enough to keep up in order to assess the current situation and project future results.

Comparisons between business models for two IT companies Image source: Flickr.com

The Demise of the Corporate Planner

Before the Internet and customer-power, there were corporate planners who made largely deterministic projections about the future of the enterprise. Before that, there were Soviet five year plans. Neither was destined for long-term survival and for the same reason: they both tried to control the uncontrollable. Today’s business model blends facts, decisions, eventualities and probabilities. About the only certainty it can offer is a measure of the amount of uncertainty it contains.

A Need for Shape-Shifting Simulations

Similarly, simulations of business situations, opportunities and threats need to be able to change as fast as reality and the collective mind of the corporation’s senior management. While computer-based models can be calculated and recalculated according to different input, changing the fundamental drivers of the model is not always simple.

Hyper-dimensional Space Travel the Easy Way

One of the features of Analytica is the possibility to add, modify and delete business model drivers in a simulation, without tears. Analytica’s Intelligent Arrays™ let users build simple or complex multidimensional models in an easier way than trying to construct them with spreadsheets or program them with other languages.

Progressive Refinement of Initial Models

From a simpler starting model, Analytica lets modelers progressively make the model more sophisticated. The sensitivity of the model to different factors can be rapidly checked at each stage. If it turns out that a factor has little influence on how the model works, it can be removed again to then simplify the model. One of the big advantages of this approach is to get a model into operation quickly, an important point given the fast-changing business models of today.

An Agile Approach to Business Model Development

Progressive refinement in Analytica is far easier than in some of the other technologies sometimes used. Spreadsheets for instance require major changes in order to extend or add to the dimensions of a model, intensive subscripting and looping. In Analytica, most of the formulas are extended automatically when models are extended without having to make any further changes. There is an analogy to be made with other IT projects that use the Agile approach to make incremental changes and keep up to date with user requirements, rather than the traditional waterfall approach that now so often runs the risk of being out of sync with the real needs by the time it finally nears completion.

If you’d like to know how Analytica, the modeling software from Lumina, can help you to keep pace with rapidly changing models of all kinds, then try a thirty day free evaluation of Analytica to see what it can do for you.

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Sean Salleh

Sean Salleh is a data scientist with experience in guiding marketing strategy from building marketing mix models, forecasting models, scenario planning models, and algorithms. He is passionate about consumer technologies and resource management. He has master's degrees in Operations Research from University of California Irvine and Mathematics from Northeastern University.

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