Streamlining tech for maximum efficiency: Avoiding unnecessary waste

Last year, we saw many organisations kick off ‘transformation’ projects ranging in scope from the aggregation of several smaller change projects, collectively badged as transformation, to attempts to transform particular aspects of a business, to enterprise-wide change programmes.

With a dizzying array of cool tech available to make a range of business processes faster and easier, the temptation is for organisations to spend ever more money on new solutions to help deliver transformation.

However, there is often substantial overlap in the applications of new tech, creating a great deal of waste in terms of engineering capacity, operational processes and overall expense. The irony is that many organisations appear to be failing in their transformational aims because they are spending too much money on too many different kinds of tech, but not addressing their core objectives.

Even with big transformation projects, delivered by leading players, clients can reach the point of achieving a minimum viable product and then run out of time, money or simply appetite - and then decide to just move on to the next big idea. No surprise, perhaps, that we find ourselves at the midpoint of 2024 in a continuing cycle of incomplete transformations which are generating a shocking amount of waste.

For example, many ExCo I have met in the past five years has been pursing some type of ‘cloud first’ or hybrid cloud strategy. But with cloud usage soaring I can’t help feeling there is a great deal of unnecessary consumption and I also wonder how many organisations have taken the time to ‘lift the bonnet’ and assess how effectively their cloud consumption is being utilised to help their business run more efficiently.

Instead, cloud capacity just keeps going up and up. With the prospect of quantum computing enabling organisations to consume much more data at a much faster rate, and with large language models and generative AI consuming ever-increasing quantities of data in order to become more effective, the need for larger cloud storage can only grow.

One problem that many organisations face is the unnecessary duplication of data, with companies ultimately paying to save those duplicates. On the one hand, it can be argued that paying for additional cloud consumption is cheaper than the alternative – cleaning up and streamlining your entire data pool. On the other hand, there are clear efficiency savings in only storing the data you need, thus paying for fewer licenses for third parties to manage your data and aligning energy use in the supply chain more closely with the organisation’s green credentials. Shadow IT has given rise to Shadow Data, but there is an assumption that AI will fix this. Rules based data triage, that isn’t AI is perhaps the key, particularly with a regulator and EU AI acts following quickly behind.

Whether we are advising clients at the outset of transformation on governance issues and assisting with change delivery, or helping them to manage a project that is already in flight, but isn’t going according to plan, the element that we find often gets overlooked is the migration of legacy data..

Organisations often run out of money before that point, but find themselves spending money on both a new platform and legacy systems, without a clear strategy for moving essential data across to the new system. They get caught on the edge of their target state, but cant make the final leap.

Projects will also suffer from scope creep, with various stakeholders in the business requesting different requirements for the a new “platform”. Strategy and vision change, so its key to ensure new directions can be achieved, but its not always the case. This can quickly create challenges down the line in terms of additional time, expense, and even the hire of new teams, to deliver separate configurations, engineering and reworking.

The extreme scenario, which we have seen in big organisations across several business sectors, is where individual business units have built their own environment, resulting in two or more instances of the same platform. Again, this can create major challenges in the future, when attempting to migrate those systems to a new single platform. Or perhaps that is a problem for the next generation of Cx leaders.

It may be that AI-powered analytics platforms will save many firms’ data strategy, where organisations have held off from adopting earlier technologies.

For those organisations that have migrated multiple platforms to a new single provider but whose data is still languishing in legacy systems, compounding the level of waste in spend (and driving up unnecessary demand for more cloud capacity) through shelling out for yet another service is unlikely to be a silver bullet. We all love exciting new tech, but sometimes there’s no substitute for keeping it simple, good advice and industry expertise.