Developing a data driven decision making strategy

We are in the age of data. The explosion of data has enabled it to become a commodity that sees data heralded as the new oil. But how many companies have successfully implemented a data driven decision making strategy? IBM conducted a global study in which they surveyed 13,000 C-suite executives. The execs were asked about the strategies they were using in order to extract value from data. The results showed that companies that had successfully integrated “data into their strategy, operations and culture are largely outpacing their peers in revenue growth and profitability”. This might not be a surprise to those of us in the data analytics space. But what might be surprising is that the results also showed that “only nine percent of companies surveyed compose this group”. So why is that so few companies are managing or able to extract value from their data?

Some of the challenges lie in the three key points of data adoption mentioned by IBM –

  • Strategy
  • Operations
  • Culture

In this data age, there is so much talk about

But what do any of those terms actually mean? Do executives really understand what is required in order to implement a data driven strategy?


Mike Bugeme’s book Cracking The Data Code – Unlock the hidden value of data for your organisation, discusses “unlocking value from data is no longer a technical challenge but a leadership one”. There is now a need for senior leadership to educate themselves on the terminology and principles of data. The appointing of a chief data officer is one of the key recommendations.

Positioned at board level gives the opportunity for the role to influence an organisation’s strategy. This is still a challenge for companies though. They continue to not hold data in high regard or who see data as an offshoot of technology, rather than a discipline all of its own. Data needs to be an integral part of an organisation’s strategy and not an afterthought. That can only realistically be achieved if there is a seat at the table for data. Just in the same way that finance and marketing and other functions do.


For non-tech organisations, it can be daunting and a potentially expensive proposition for them to put in place the infrastructure needed to make the most of their data. Programmes of this order of magnitude have historically been known to overrun. Or they come in over budget, while having not delivered what was promised. But there is no longer a reason for that to be the case. Cloud technology, agile software development methodologies and the advent of no-code or low-code platforms have changed things. With focus, organisations can adopt a data driven approach much quicker and cheaper than previously possible.


The big data/tech companies have ensured that data is an inherent part of their company culture. Of course this would be expected of these companies. but the point is that there is a lot that non-data/tech companies can learn from the FAANG companies. Employees of these companies, whether they be in engineering or not, are educated in data.

They are taught the importance of data to the organisation. Training and tool sets are provided, in order to develop the skills that are required for a data driven mindset. Other companies don’t have to replicate this model. Technology has advanced to the stage where augmented intelligence is a very real possibility for many companies. The best data driven strategies take a hybrid approach. In these scenarios, the best of human capability is combined with advanced data analytics techniques. Of which the end result is the creation of new and evolving solutions.

In maturity terms the data age has only just begun. The possibilities are significant for those companies willing to adopt a data driven strategy. There are barriers to entry to implement and execute this type of strategy. But they are low and are getting lower all the time. The only consideration is then whether organisations are willing to become leaders rather than followers in a new data driven world.


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