Most large organisations have already made large investments in data. Richard Graham explains why he thinks, in many cases, there's still work to be done.
Many large organisations understand the potential of data, and often have a broad range of data and analytics capabilities that they are using to become data driven.
However, what we hear from clients is that very few of them feel that the return on investment, or the scale of expected value, is really being delivered from these large investments.
When we look at the underlying reasons why, it is clear that in order to realise the value requires a much wider shift in terms of approach and collaboration across all areas of a company's operating model.
In particular, the relationship and processes between the Data Science teams building advanced analytics, and the IT teams deploying, embedding and supporting them for production use.
Understanding and considering the full information life cycle and understanding where to prioritise development of capabilities - with maturing a collaborative approach - is key.
What Approach Should Organisations Consider?
Organisations need to take a two-speed approach to rapidly innovate and develop advanced analytics use cases whilst maturing the operational processes to support and optimise them.
This is often a significant change for businesses, so we recommend adopting an approach that defines the target operating model but delivers it on a small scale, with a view to scaling as the use cases and operational maturity improves.
Done the right way, with the appropriate governance in place from the start, you will have the agility to be able to improve the impact and speed of taking analytics to market whilst maintaining standards, controls and quality within acceptable risk tolerances.
Without this, companies risk over-complex and over-priced investments, or worse case, impairment of an investment deemed impossible to sustain.
What Are Common Challenges & How Can Organisations Overcome Them?
The biggest challenges are not about the technology but tend to be about approach and collaboration.
Focus needs to be on a clear strategy and roadmap for data initiatives, that delivers tangible value quickly, whilst keeping the wider strategy and long-term improvement in capability in mind. This should also include a dedicated effort to improve data literacy across the business.
To that end, its important that companies create a clear data strategy, aligned to business strategy and value, and with Board level sponsorship.
It's also important to note that this will almost certainly require changes across the organisation, and should not become yet another silo of accountability that sits within IT.