Quantum computing.

What quantum computing is

Quantum computing is an approach based on the principles of quantum mechanics. A conventional computer works with bits: at any moment each bit equals either zero or one. A quantum computer works with qubits, which can be in several states at once.

This leads to the main practical difference. A classical computer goes through options one after another; a quantum one processes many options in parallel. For tasks with an astronomical number of options this means a fundamentally different speed.

It is important to understand the limit: a quantum computer is not “faster” than a conventional one in general. It is faster on a narrow class of tasks - search, optimisation, modelling. For most everyday computing it has no advantage.

Let's look at what this technology could in principle bring to working with data, why it is too early for small businesses to plan around it today and what is genuinely worth doing instead of waiting.

Where this technology could be useful in analytics

Data analytics runs up against volume: the more data there is, the more expensive it is to process and the longer you wait for a result. Classical methods solve some tasks only approximately precisely because an exact solution would take too much time.

Quantum computing promises to remove this limitation for several types of task:

• Optimising complex systems. Splitting a budget across dozens of channels, delivery routes, production scheduling - tasks where the number of combinations grows like an avalanche.
• Modelling processes. Market behaviour, how demand reacts to a price change, development scenarios - wherever there are too many variables for an exact calculation.
• Demand forecasting. More accurate models thanks to taking more factors into account at the same time.
• Personalising offers. Choosing the best option for each customer rather than for a segment.

The word “promises” here is no accident. This is a direction of research, not a ready-made tool with a price list. How working with data is organised today and what decisions it already makes possible is covered in our article on the role of analytics.

Why it is too early for small businesses

Let's be direct: as of today, quantum computing is not a tool for small and medium-sized businesses, and there is no need to budget for it. There are several reasons.

The first is access. Quantum processors exist in research centres and in the cloud services of large technology companies. This is not a boxed product you can buy and roll out.

The second is the type of task. The advantage shows up where the number of options is genuinely enormous. A company with one warehouse, three advertising channels and a customer base of a few thousand simply has no such tasks - an ordinary spreadsheet handles them.

The third is expertise. Working with quantum algorithms requires training that neither a marketer nor a regular analyst has. It is a separate profession.

The fourth, and the main one: almost every company has cheaper ways to get more value from its data. As long as enquiries are logged in three different places and advertising spend is not reconciled with revenue, any talk of quantum computing is premature.

What to do with your data now

The practical programme for the next few years looks more boring, but it delivers results.

1. Bring your data together in one place. Enquiries, deals, traffic sources and advertising spend should flow into a single system rather than living in e-mail, a messenger and a notebook. Why this matters is covered in our piece on CRM.
2. Learn to measure return. Link the spend on each channel to the money it brought in. The method is described in our article on analysing data.
3. Test hypotheses with experiments. Comparing two variants on a real audience gives more than any modelling. The procedure is in our piece on A/B testing.
4. Use the algorithms that are available. Automated strategies in advertising platforms and neural-network-based tools already work and do not require a research lab. More on this in our article on AI in marketing.

These four steps cover most of what people usually bring up advanced technology for: understanding what works, and the ability to make decisions based on numbers rather than gut feeling.

One risk worth knowing about in advance

There is one area where quantum computing will affect business sooner than analytics - data protection. Many of the encryption methods in use today rest on the fact that certain calculations are practically impossible to complete in a reasonable time. The arrival of sufficiently powerful quantum processors will weaken that foundation.

For a company this means not urgent action but attention to the topic: updates to security protocols will have to be adopted over time, just as any security updates are adopted. Why customer trust is directly tied to protecting their data is covered in a separate piece.

The flip side is that the same technologies bring new methods of protection. As with any change of technological generation, the winner is the one who keeps track of the changes, not the one who tries to outrun them alone.

How to follow the topic without unnecessary spending

The sensible position for a small company is to watch rather than invest. A few practical markers.

The first sign that the topic has come closer is the appearance of ready-made services where the result is available without understanding quantum mechanics: you send a task and get an answer. Until then, the technology remains a subject of research.

The second is industry examples. When case studies with numbers appear from companies of your scale rather than from research institutes, it will be possible to assess applicability.

The third is healthy scepticism about wording. “Quantum” in the description of a marketing service today almost always means ordinary algorithms with a loud name. Such claims are worth checking with the same questions as any other contractor's promises - more on this in our piece on promises in digital.

The technologies that are genuinely changing how we work with data right now are the ones we explore in our special projects and custom solutions - where an off-the-shelf tool does not cover the task and something has to be built from scratch.