Opinion by Thought Leaders
Read the latest opinions from tech & business pros across the globe.

Small Business Needs More Diversity in Leadership

 

In a not too distant past, diversity at the leadership level was not as common; nor was it commonly agreed upon beneficial practice. Though still not at desirable levels such practices are more widely discussed and accepted. However, most discussions around diversity tend to be around midsize and larger organizations; supposedly having a “trickle-down effect” if those larger organizations lead by example.


Before going into its necessity for small business, let's agree on a couple of simple principals for this article:

  • Diversity should almost never come at the expanse of qualification.
  • Diversity is proven to have a positive impact on revenue and profits.

Now that we have established some ground rules, let’s move on to why small business should be the main place where inclusion and diversity takes place.

Why?

It doesn’t matter what school of thought you prescribe to and it doesn’t matter where you look: small business is the backbone of United States economic growth engine. It equally employs the largest number by leaps and bounds. So one would wonder why we expect large companies to lead the way of having more diverse and inclusive leadership. The answer is: we shouldn’t. We should expect diversity and inclusion to “trickle up” from small businesses not only because of their unparalleled dominance but even more importantly because of their inherent flexibility, nimbility and adaptability.

How?

So, since Small Businesses (SMB) are so dramatically dominant how would or should they go about such diversity and inclusion? Most of the conversations on SMB starts around entrepreneurs and their ability to succeeded in highly competitive markets where the competitions is not static: not only is it likely that they are already either competition with established businesses but also trying to create interruptions, but they also have to wrestle with the traditional challenges of SMB including funding, human resource management, production and quality assurance as well as consumer dynamics.

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Are You Maximizing Your Investment in Your Experts?

 

In the ever-evolving business world in which technology enables rapid changes and evolution providing more robust tools, paving the way for better and more effective business management, it is hard to argue with the impact of prospective. Be it the burning the desire to be more data driven or the ability to have near complete operational awareness; the access and subsequent analysis of such data is likely to result in even more questions and potentially more doubt about the validity of such analysis. Without going into intrigues of data analysis and bias i.e. information bias, selection bias, and confounding, let’s have a look how it can be reasonably mitigated in a startup setting.

The basics

Let’s start with a realistic assumption: startups have some inherit limitations, mainly around resources i.e. funding and attraction of high quality talent. Both of those are equally relevant to decision making at macro and micro level, hence it stands to reason that decision making at both levels are limited. This particular conclusion, though semi subjective has a real impact on the explicit and/or implicit expectations of virtually all stakeholders.

Mitigations

Once the realization of those limitations are taken into account, the next step would be seeking a method to mitigate those perceived shortcomings. The usual reaction tends to be an increase in resource allocation to either tools or human capital; and frankly there is nothing fundamentally wrong with that approach. However, it raises the questions about feasibility, effectiveness and efficiency.

Human capital vs tools

It is no secret that previously mentioned advancements in business related technology has resulted in an amazing array of advanced and sophisticated tools that allow even non experts to compile, visualize and interpret a wide range of data points. The real question is however the utility and impact: can such tools replace expertise? The answer is not straight forward: generally speaking, even amazing tools that democratize availability of complex data cannot be expected to provide appropriate strategy within the context of individual organizations. Sure, the data sets and factual conclusions that are not a matter of “opinion” are a great start; but how the decision makers can use that business intelligent in the context of specific setting are a point of contention.

Tools, no matter how sophisticated are truly at the mercy of the user. We all have heard the expression – tools are only as good as the user; and there is a lot of truth to that. Simple factor such as the breadth and depth of the tool its elves can have an immense impact on the output; which brings us back to the human capital i.e. expertise. But does that imply that human capital re: expertise trumps tools? Again the answer is not that “black and white”: essentially those two function symbiotically. In an optimal setting the end user has an expert level knowledge of the tool combined with matching expertise to use the conclusions both tactically and strategically in context of the field and said organization.


External vs. Internal

Now that we logically concluded that the said expertise has to be in context in order to maximize the output of the tool, it is important to explore the human capital strategic impact.

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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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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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