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Growth and Scaling Downfalls – Part V Final Thoughts

In the last few posts we touched on Growth and Scaling preparations in terms Human Capital Management, Financial Resource Management, Strategy Management and Project Evaluation Management. In the last post in the series we will touch on additional practical considerations.

Limitations

All said and done, there are many limitations that are outside the control of any organizations including market and competitor behavior, consumer perceptions, external stakeholder objectives as well as rapid innovations. Those and many other factors that shape the overall perceived and real “business environment” that will inherently have an influence on the outcome of any business related project. Hence it is vital to account and plan for certain margin of error that will dictate changes, adjustments and pivots.

Expectations Management

Though a stable tool of business management, expectations management is one of THE most important yet clearly underutilized component of scaling and growth projects. Drawing on the idea that there are inherently many more unknowns in those projects that can lead to limitations, it is extremely vital to utilize both the theoretical and practical aspects of expectations management theory.

Diminishing Returns

Growth is NOT unlimited nor is Scaling. Contrary to the belief that there is no ceiling to expand and grow, the reality is much different. As mentioned previously, the sheer fact that are many components outside the influence of an organization, it is rather logical to see why there are real life limitations. Hence it is extremely important to start off those growths and scaling projects with reasonable outlook and goals.

Business Process Engineering (Reengineering)

When limitations and expectations management are accepted and implemented, process engineering and reengineering become indispensable. In line with other component, business process management, engineering and reengineering have an even more outsized role when it comes to scaling and growth in order to address and accommodate both the limitations and expectations management.

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Growth and Scaling Downfalls – Part IV

 

In the previous post “Growth and Scaling Downfalls – Part III” we discussed strategy aspects of a scaling project. The next topic on the scaling preparation “to do” list is measuring success and failure.

Scaling and growth both depend a great deal on experimentation: be it at tactical level deciding who will do what to strategic level defining success or failure. That being said that kind of decision making naturally requires a great deal of analysis; qualitative or quantitative.

Quantitative

Data driven quantitative analysis is or should be the basis of virtually all business decisions. Though an established field, the quantity of data that has been previously inaccessible or impractical for usage has changed the field. The same quantity of the data sets that are now available have also created several other side effects for small and mid-size organizations; ranging from increased cost for proper analysis to “analysis paralysis”. Hence, the usage has to be defined in terms of practicality: both the collection and analysis of data have to be defined within the context of cost and impact.

Qualitative

In a previous discussion about decision making we discussed the usage of qualitative decision making. Those parameters previously discussed i.e. strong pattern recognition as part of the qualitative decision making are particularly applicable when it comes to growth and scaling. In practical terms it translates to a combination of using practical experiences both industry related as well as general business experiences to decide on both tactical and strategic level: the industry know-how combined with generic business experience will provide the sort of “umbrella” coverage that will leave little room for “guessing”.

On the front line

Interestingly enough there are some unique aspects to data usage when it comes to scale and growth: though the basic methodology of collection and analysis is the same, the decision making direction should entail a more dynamic version of “bottom to top” or “top to bottom”: Micro decisions vs. Macro decisions: 

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