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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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Growth and Scaling Downfalls – Part III

 

In the previous post “Growth and scaling downfalls-Part 2” we discussed human capital aspects of a scaling project. The next topic on the scaling preparation “to do” list is strategy.

Though strategy is understood to be a vital part of any business project, when it comes to scaling and growth, it takes an entirely more fluid role: both macro and micro strategy have to be substantially more adaptive and flexible.

Macro strategy

Though the term is more widely used in financial industry, it similarly applies to the concept of business strategy at large. For this discussion “Macro Strategy” is to be understood as the “general strategy” that defines the overall approach based on organizational philosophy, culture, goals and methodology. In context of growth and scaling, “Macro Strategy” similarly refers to general organizational approach both in theory and practices as how to approach any given project.

So, why does it matter?

Essentially, the macro strategy will dictate the overall approach through the lens of organizational mindset; which includes factors such as cultural, social, structure and flexibility. It can also be shaped by outside factor such as target market, brand perception as well as industry specific norms and standards.                                                                        

For instance, an organization that is dead set on market domination is less likely to be deterred by its competitor’s abilities, approach or resources. Hence, the Macro strategy may have an oversized impact on the initial planning of growth and scaling.

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Growth and Scaling Downfalls – Part II

 

In the previous post “Growth and scaling downfalls” we discussed human capital aspects of a growth project. The next topic on the scaling preparation “to do” list is financial resources.

It goes without saying that pre-planning for financial resources needed to meet scaling goals is not only essential for obvious reasons, but it also important in contributing to both tactical as well strategic decision making.

Who?

So, who should be involved? Granted that there many different methods, it stands to reason that such determination should be a “top down” approach, as in starting with the project manager. Additional team members should include project sponsor, member of operations management as well as finance. Of course, it is understood that the CFO (used here generically to refer to the leadership of the financial division) had to be involved in the initial SOP creation for such projects.

How?

The mechanics of a budget creation are certainly widely known and not a subject of this discussion, however there are couple of points worth mentioning:

• Realistic budgeting: one of the rather common issues in budgeting for growth is the ability to understand the nature of such project. It is extremely vital to understand that unlike other projects, the uncertainties in growth and scaling dictate building a larger margin of errors into the budget.

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Growth and Scaling Downfalls – Part I

Many of us have either been part of a “growth and scaling” project or have led such efforts. We all have some battle stories of what worked and what didn’t; yet we hardly ever hear about the preparation that goes into a successful “growth and scaling” project. In this series, I will address several of more important considerations and factors.

The Beginning

Scaling and growth both as principal as well as in practice are simply a function of evolution: a given organization reaches some specific benchmark that leads to a need to grow the business. Those benchmark can be as objective as following a road-map that specifies steps or as subjective as the executive team deciding it is time. Without exploring the details of the decision making, let’s look at one of the most fundamental factors: The Team.

The Evolution

Even without extensive business experience, logic simply dictates that growing or scaling a business can only be successful when the said business has the resources, i.e. human capital and financial means. To keep the discussion on point, I will forgo discussing the bootstrap version of this topic. 

Human capital or the team that is going to be in the front line of those growth/scaling efforts needs to be able to execute the directives that are designed to stimulate and augment the overall growth path. In order to do so some basics, have to be in place:

• Quantity: the team size has to be realistically feasible in relations to the workload

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Best Decision Making - Experience Versus Data-based?

 

The daily life of any executive entails an endless amount of decisions: those decisions are made based on factors such as experience, data, organizational needs and goals. Those decisions are likely to be additionally impacted by the ever increasing demand for speed. Hence creating a tempting environment to excessively rely on decision making based on experience. This begs the question: does relying on experience as sole point of reference for decision making viable? And if it is, how do we maximize the odds of better outcome for those decisions?

Variety of experience

It is a fair to stay that we all perceive reality differently: people can be in the same situation or conversation yet have an entirely different take away. The same applies to “experience”; one single instance of “experience” can be sufficient to deter or encourage a particular action based on the perceived “lesson learned”; it is even entirely possible to classify the same instance of “experience” as good or bad solely based on the perception of the experience and/or its outcome. This leads us to the question: if the said experience is the basis of one or more decisions, how can potential errors or bias be minimized?

Single or multiple experiences

It goes without saying that a single instance of an experience is rather a debatable proposition when it comes to decision making. It should be rather obvious that a single instance of “data point” be it qualitative or quantitative can’t possibly be considered as reliable basis for fundamental decisions. That being said when can experience be reasonably viable? Is it a functional of quantity? Quality? The answer is not that one dimensional. 

A single instance of virtually anything can signal flawed results and conclusions because there are many variables that can change the actual and or perceived outcome. Some of those factors include stakeholder’s behavior and actions, circumstantial organizational resource limitations and or allocation as well as interpretation biased by multiple level of internal and external actors. Hence, logic dictates that one, two or any quantity of an experience is susceptible to flawed conclusion analysis.

Patterns

So, if even multiple instances of a given experience can’t be relied upon, what is the solution? One possible solution is reliance of patterns; this method would strip away a lot of the shortcoming of utilizing the experience or experiences as a data point by looking at common denominator’s as opposed to evaluating the experience in its entirety. Additionally, it would allow for larger set of qualitative data points because it eliminates the necessity of using only personal experience as opposed to being able to include external and/or third party input even unrelated to specific projects and/or industries.

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