Back “The biggest hurdle to digital transformation is not the technology, but the speed at which companies can implement it.” (Quote: Harvard Business Review) This statement strikes a chord. Because it shifts the focus away from the mere availability of new tools towards a far more important question: how quickly can an organisation turn opportunities into tangible results?
In many companies, the diagnosis has long been clear. Processes are too slow, media breaks cost time, data is locked away in silos, skilled staff are working with tools that do not allow them to realise their full potential, and customers have long since come to expect real-time digital services. The answer often seems clear too: new platforms, new software, new AI solutions, new automation. Yet this is precisely where the real problem begins. It is not innovation that is lacking, but the ability to translate it into operational reality.
Technology is available, but implementation is in short supply
Today, companies have more technological options at their disposal than ever before. Cloud platforms, low-code approaches, workflow automation, AI-powered assistance systems, data-driven decision-making models and integration solutions for almost every use case are available. The question is no longer whether something is technically feasible. The question is how quickly it can be introduced, adapted, accepted and scaled.
This is precisely where pioneers differ from laggards. Pioneers manage to treat digital solutions not as one-off projects, but as an ongoing capability. They establish structures that ensure innovation does not get bogged down in pilot projects, but becomes productive. Laggards, on the other hand, confuse activity with progress. They invest in tools without creating the organisational conditions necessary for speed.
Speed is not an end in itself. It is a competitive advantage. Those who learn faster, integrate faster and roll out faster can react to market changes before they become a risk. In regulated sectors such as insurance, finance or healthcare, this capability is particularly valuable, because complexity, compliance and legacy systems further slow down change in these areas.
Why companies fail when it comes to speed
The causes are rarely purely technical in nature. They often lie within the organisation itself. Responsibilities are unclear; business units and IT work alongside each other rather than with each other; decision-making processes are too lengthy; and budgets are allocated too heavily to individual projects rather than to platforms and capabilities. Added to this are legacy system landscapes in which every change creates knock-on problems.
Another factor holding things back is the fear of making mistakes. Anyone who wants to get every digital initiative perfect from the outset wastes time. Yet digital transformation thrives on an iterative approach. Small, effective steps are often more valuable than grand concepts that spend months in coordination loops. Companies that spend too long planning are overtaken by those that test, learn and adjust more quickly.
Speed also plays a central role culturally. In many organisations, stability is rewarded more highly than change. Whilst this is understandable in traditional operating models, it leads to inertia in dynamic markets. Digital transformation therefore requires not only new systems, but also a new understanding of collaboration, responsibility and the ability to learn.
Modernising legacy systems rather than blocking them
This point is particularly relevant at insinno: many companies do not have to start from scratch, but must work with existing systems that have evolved over the years. Legacy systems are not the problem in themselves. The problem arises when legacy systems become an excuse to delay change. Modern transformation approaches therefore focus on evolution rather than radical renewal.
This means: decoupling processes in a targeted manner, standardising interfaces, making data flows visible and integrating new functions step by step. It also means not replacing existing applications prematurely, but rather assessing which parts remain valuable and where modernisation offers the greatest leverage. Taking this approach gains speed without jeopardising operational stability.
Architectures that support scalability and adaptability are particularly effective in this regard. Cloud-native building blocks, API-first approaches, workflow orchestration and automated deployments can significantly increase the speed of transformation. However, it is not the buzzword that matters, but how well it fits the organisation. Technology does not need to be spectacular; it simply needs to be interoperable.
Speed requires clarity
Anyone who wants to move faster needs more than just tools. They need clarity on goals, priorities and responsibilities. Which processes deliver the greatest benefits when digitised? Where do the most costly inefficiencies arise? Which use cases create measurable value for customers or staff? And which areas are ripe for automation, AI or workflow optimisation?
The answers to these questions need not remain abstract. On the contrary: the more precisely a company understands its levers for change, the faster it can act. Rather than launching large-scale transformation programmes with unclear outcomes, a focused approach is more worthwhile. A clearly defined process, a measurable business case and a realistic roll-out plan are often the quickest route to visible results.
Clarity also means accepting the right level of maturity. Not every organisation can immediately make everything cloud-native, fully automated and AI-supported. But every organisation can begin to modernise systematically. Small, successful steps build trust and lay the foundations for larger changes.
AI is not a magic shortcut
Particularly amidst the current hype surrounding artificial intelligence, the concept of speed is often misunderstood. Many hope that AI will automatically compensate for organisational weaknesses. Yet AI primarily amplifies what is already in place. Good data, clean processes and clear governance make AI valuable. Unclear responsibilities, poor data quality and fragmented landscapes make it difficult.
That is why, in digital transformation, AI is not a substitute for structure, but rather an accelerator for mature organisations. Where processes are already standardised, AI can have an enormous impact, for example in the classification of tasks, the extraction of information, decision-making preparation or day-to-day support. Where structures are lacking, however, new complexities arise.
This quote reminds us that technology does not automatically mean transformation. Only when companies increase the speed at which they adopt, test and integrate new capabilities into their day-to-day operations does technology realise its true value.
What companies should be doing now
Anyone taking digital transformation seriously should focus not just on tools, but on the ability to implement them. Three questions can help with this:
- Where are we currently wasting time due to manual processes, media breaks or unnecessary coordination?
- Which digital measures will deliver measurable benefits within weeks or months?
- What organisational hurdles are preventing good ideas from becoming productive quickly?
The answers to these questions often reveal more clearly than any technology roadmap where the real need for action lies. Digital transformation is successful when it evolves from a project into a capability. And capability means: recognising faster, deciding faster, implementing faster.
Conclusion
The real challenge of digital transformation does not lie in finding the right technology. It lies in structuring an organisation so that it can deploy technology effectively and swiftly. Speed is not just a buzzword here, but a strategic factor. Those who master it can reduce complexity, scale innovation and build competitive advantages.
For companies such as insinno, this is a key focus: not just advising on which solutions are possible, but ensuring that they are actually implemented. Because ultimately, it is not the potential of a technology but the speed of its implementation that determines its value.
