Abstraction to Action: Flexible Strategies for the Cloud Era

It’s become almost a mantra in cloud adoption circles: define your business goals before you begin. And it’s sound advice. Setting clear objectives can help you avoid aimless technical experimentation and keep your cloud journey aligned with tangible outcomes. Indeed, one of the worst mistakes that we see is that companies have embarked on a cloud migration purely because it's "what people are doing now" without enough though about where it will take them.

But here’s a thought. What if the very technologies driving this transformation – the cloud and now, increasingly, AI – are changing the nature of the goals themselves? What if, before we ask “How do we achieve our business objectives with cloud?”, we pause to ask, “Are these still the right objectives?”

This isn’t a rhetorical flourish or an attempt to be wilfully contrarian. It’s a reflection on a simple but often overlooked reality: strategy is built on assumptions, and technology at this scale tends to make those assumptions quietly obsolete.

Questioning the Foundations

Business goals don’t emerge from the void. They’re informed by how an organisation defines itself: what it believes it does, who it believes it serves, and how it believes it delivers value. If the tools and possibilities available to you change dramatically, it stands to reason that your self-definition – and therefore your goals – might benefit from a second look.

Suppose a company has historically offered a wide range of IT services to local businesses—everything from infrastructure setup to software support. This jack-of-all-trades approach worked well in a limited market. But with the availability of global cloud infrastructure and digital delivery models, the company now finds it can focus solely on one specific area—for example, data analytics for the retail sector—and still reach enough clients to make it viable, even profitable.

Alternatively, suppose a company has historically specialised in one slice of the customer journey, like running a secure payment platform. With the rise of cloud-native integration and scalable automation, it might now be in a position to expand its offering—managing the full transaction flow, all the way from shopping cart to compliance and beyond.

In both cases, the issue isn't that the original strategy was flawed. It's that the context in which it was formed has shifted.

Abstraction: Not Just for Developers

Let’s borrow a concept from software engineering for a moment: abstraction. In programming, abstraction allows you to simplify complex systems by focusing on the parts that matter for a given task. You don’t need to know how the electricity grid works to use a computer; you just press the power button.

Above all else, cloud computing is built on the notion of abstraction. It removes the need for most businesses to worry about infrastructure, letting them focus on delivery, outcomes, and user experience.

But abstraction doesn’t need to stop at the technical layer. I’d even go as far to say that it shouldn’t stop there and that it should be applied to everything, including the business itself.

At Public Cloud Group (PCG), we often find that helping companies adopt the cloud involves more than just replatforming applications. It means thinking carefully about what the business is actually trying to achieve. What problem are they solving? What need are they fulfilling? Sometimes, the answer has less to do with IT modernisation and more to do with strategic clarity.

This echoes a point made decades ago by Philip Kotler and Theodore Levitt in marketing: don’t necessarily define yourself by your product; you can also define yourself by the customer need that you serve. Are you selling ball bearings, or are you in the business of reducing rotational friction in industrial machinery? The latter opens more doors. It’s an act of abstraction that lets you see the forest instead of the tree you’ve been polishing for twenty years.

Thinking Across Disciplines

This strategic act of stepping back – of questioning what you think you know – is not unique to technology or business. You see it in archaeology, for example. The archaeologist collects fragments, tries to place them in context, and builds a model of a past world. But when a new piece of evidence turns up, the interpretation must shift. The trick is knowing when a new piece is a one-off anomaly and when it's a sign that your entire framework needs adjusting.

In military strategy, the idea is similar. Novelty is not inherently good and sometimes conventional methods work just fine. It should go without saying that one of the worst mistakes a general can make is to think of a clever plan that will definitely fool the enemy - but that none of the officers understand and none of the troops are trained to deliver.

Other times, however, in can be that the battlefield has changed and the general who sticks to yesterday’s doctrine will find themselves decisively outmanoeuvred. The challenge is knowing when the terrain has changed enough to justify a new approach and be ready for it.

Even in science, abstraction is a double-edged sword. Models are helpful, until they aren't. Once again, the optimal strategy lies not in building the perfect abstraction, but in knowing when it no longer fits reality.

In all these fields, the message is clear - strategy isn't just a matter of logic. It's also a matter of interpretation and timing.

Seven Strategic Principles for Times of Flux

So, if cloud and AI are changing the terrain, how might one respond? Here are seven thoughts – not rules, but principles worth considering.

• Recognise the Shift
  First, take stock. Are your existing strategies still based on an environment that no longer exists? The presence of cloud infrastructure and AI capabilities might have quietly altered your competitive landscape, customer expectations, or operational constraints.
• Preserve Flexibility
  If you’re in the middle of change, rigid optimisation can lock you into the wrong outcome. Design your systems, teams, and goals to allow for course correction. Flexibility isn't a sign of indecision; it's often a prerequisite for long-term clarity.
• Make Sense Before Acting
  In periods of uncertainty, the first job is not to act, but to understand. Use low-risk experiments and small-scale pilots to test ideas, gain insight, and avoid committing prematurely.
• Balance Exploration and Exploitation
  Refine what works but also invest time in trying new approaches. The cloud makes experimentation cheaper; the challenge is making sure it’s purposeful. Allocate resources to both maintaining core value and uncovering future opportunities.
• Reframe the Question
  Sometimes, the problem isn’t the solution you’ve chosen, but the question you’re trying to answer. Instead of asking, "How do we optimise delivery of X?" consider, "Is X still the right thing to deliver?" The difference is subtle but important.
• Invest in Capabilities, Not Just Outcomes
  Technologies change. Markets shift. What endures are capabilities: the skills, platforms, and ways of working that let you respond to change rather than be flattened by it.
• Validate Novelty Through Usefulness
  Being new is not the same as being valuable. Cloud and AI open many doors, but always resolve to walk through the ones that lead somewhere useful. Hype fades fast; utility doesn’t.

Curiosity as a Strategic Asset

What the cloud offers is not just computing power, but the chance to reconsider what you’re doing with it. It abstracts away many traditional constraints, leaving you with a blanker canvas than you're used to. The temptation is to fill it quickly. The smarter move is to step back and ask: What picture are we really trying to paint?

Strategy, in this context, becomes less about prediction and more about perspective. And perhaps the most strategic act of all is simply to stay curious.