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A Proof of Concept (PoC) is a high-value component of software development projects.

It’s a time-bound, fixed-scope exercise that tests the feasibility of a technical concept using measurable goals and success metrics. PoCs act both as a way for organisations to discover and learn about new technologies, and a way for organisations to manage the risks associated with exploring new technologies. However, as with any project, PoCs entail inherent limitations and pitfalls that can create cost, time and resource implications. Here’s my top 3.

1. Lack of business readiness.

One of the main pitfalls with a PoC is the inability of the broader business to adapt to the new capability it demonstrates. In practical terms, this can mean that a level of business transformation is often required beyond the original scope of a PoC, to adopt to a new technical system or process. It may be as simple as individual employees changing their workflows, or as complex as reconfiguring multiple business units. This can lead to a sort of ‘false positive’ from a successful PoC: the concept may be technically feasible, but broader adoption may present obstacles.

It’s vital to consider business process change when implementing a PoC into production, and is a crucial consideration in how an MVP (Minimal Viable Product) should be scoped.

2. Defining the wrong success metrics.

Technology is just a tool. Selecting the right tool for the right job is dependent upon having identified the right job to begin with.

Creating a PoC to answer a broad technical question - rather than applying technology to identify a specific business question - is a common pitfall. Consider the statement:

“Let’s see if we can use Machine Learning in Azure to help our business”

This is a difficult thing for a PoC to prove as it has no clear outcome, and it pre-supposes that Machine Learning is the right tool to solve this undefined need. Instead, we could add clarity to our goal by reframing:

“Let’s see if we can use Azure Data Services to help reduce time spent producing financial reports.”

This is a good starting point, and we can quickly refine the key technologies that need to be proved and simple ways of measuring the factors that define success. Good problem statements for PoCs are as specific as possible, often dealing with the viability of very low-level technical challenges such as integrations or data migrations with very narrow success criteria.

3. Building a PoC for production.

It is common wisdom that a PoC should not be put into production. Although this is almost completely true, it is an often-misunderstood statement. A PoC is immediately compromised if it is built to be productionised. This is because the additional considerations and work entailed in creating a production-grade solution adds significant overhead without knowing if the solution is even feasible, often increasing costs and risk against an uncertain outcome. However, if a PoC is deemed a success, that does not mean all the work undertaken needs to be thrown away by default. It means it can be objectively evaluated, and any viable component parts can be reused and carried forward into a follow-on project to build a production-ready MVP.

Moving to a production-grade solution means a much greater focus on code quality, reusability, security, testing and NFRs (non-functional requirements) among other things. Whilst all imperative in production systems, these will often add little value to the goals of a PoC. However, it is always wise during development to adhere to best practices to maximise the potential for possible expansion and refactoring, preventing the solution from becoming entirely disposable.

A good PoC will be rooted in a business value-based outcome and undertaken to prove that the proposed capability through a new application of technology or data is not only realistic, but the proposed approach is also feasible.

In 2008, as the global economy was falling apart week by week and nobody had any real idea what the next month would look like let alone next year, I had a debate-over-drinks with a colleague that focussed on whether Google had peaked, and what the future of tech might looked like against a bleak economic backdrop.  

A little context: at that point Google was effectively a cottage industry (compared to where it is today) with a market cap of $200bn and the largest company in the world was Walmart at $400bn. There wasn’t a single tech company in the top 10 of the Fortune 500. Apple had just released the first 3G iPhone and opened the App Store. Facebook had only just overtaken Myspace as the largest social network.

It wasn’t obvious when surrounded by doom and gloom and a market dominated by oil and industrial conglomerates what the future held for the technology sector, and good arguments could be made (and were) for its future in either direction. How much could ’search’ really be worth? How big could ‘websites’ be? What did the future of our careers and industry look like?

Fast forward to 2021 and Google has grown 10x to a market cap of $1,900bn. Almost 1/4 of the American economy is powered by the 4 largest global tech companies. Software and data engineering are among the highest paid and most sought-after employment sectors. The smartphone is universal. The remote worker is king. The age of the tech conglomerate is upon us. So, times are good for tech. But the question of what the future looks like for the industry is just as relevant today.

In my opinion the answer to that question is simple. The long-term impact of technology on the economy and businesses is going to make where we are today look trivial.

We’re just getting started…

In the last 100 years, the industrialisation of agriculture has driven the percentage of the population in developed countries working in food production from over 50% to less than 3%, whilst output has skyrocketed. The next hundred years is going to frame many similar stories. The number of people working in blue-collar jobs like logistics or retail, or white-collar jobs like finance or law who stand to have their industries similarly upended is huge.

This isn’t to paint a picture of rampant unemployment: every time a huge economic shift has happened, new and previously unimagined sectors and jobs are created, and the creation of wealth broadly pulls societies forward (albeit at a very uneven cadence). Rather, it’s about the sheer amount of economic output that is poised to be captured and absorbed by the technology sector in the coming years. If you could liken the current technological revolution to the prior 200-year Industrial Revolution we’re at the stage where people were still working out the basic ways the new-fangled steam engine could be used.

For better or worse, the march of technology is unwavering, and the pace of change is only accelerating. Even in the face of huge environmental shifts, to think that tech growth will stop, slow, or become less relevant seems naive. But we are human, and our capacity to understand the longterm horizon and the massive sweeping socioeconomic impact of years of technical development will evolve in parallel over time.

Technology enables businesses to deliver their purpose or mission through a different, more efficient set of capabilities. The mission of a logistics company could be stated to be as simple as getting material successfully from one point to another. Trucks, trains and boats are still the core enablers of this mission, but the capabilities that surround them are going to shift seismically. A world with global just-in-time capability and a fully autonomous transport and travel network is an inevitable future whose impact would dwarf even the advent of the smartphone. Like the smartphone, the keys to that future lie in the hands of technology companies – which make it not a case of ‘if’ but ‘when’.

How should businesses strategise against this backdrop?

Nature always provides the best analogies, so consider the house threatened by flood. Knowing the water is rising is one thing. Knowing how to save your house is another. Knowing how to take advantage of the incoming water is something else entirely. But the longer you have to plan and act, and the greater your understanding of the horizon, the less likely you are to be swept aside. Set 5, 10 and 20-year perspectives and adjust them continuously against the pace of change and emerging opportunities and threats – it all comes down to timing. To me, a realistic and informed technical strategy is one that allows you to make decisions for today against the backdrop of tomorrow. By way of an example, becoming a software-defined business might feel either irrelevant or at a huge remove from where you are today, but ultimately it’s inevitable, so why not take steps now, however small, in that direction?

So, is technology that valuable?

Technology is going to fundamentally transform almost every facet of industry and day-to-day life at a faster and faster pace, absorbing more and more of the global total economic output. In my opinion there are essentially no sectors in which the single most important question in the next few decades isn’t how to adapt to and leverage the monumental shifts technology is going to impose. The choices, decisions and strategies being made today are going to form the foundations of the next generation of fortunes.

In summary – yes.