PBT Group thought leadership
Increasingly difficult economic conditions are putting companies under pressure to find more efficient ways of streamlining operations. This has put renewed focus on the importance of data analytics as an enabler to remain competitive.
Data has long been likened to being the ‘oil’ of the information age. With the growth of knowledge workers and the number of data sources available to decision-makers, its relevancy cannot be underestimated. In this new digital environment, it has become less a case of how to find data but instead how to manage and analyse it effectively.
Having the right data can assist businesses in getting through these difficult economic times and market conditions. This requires putting the correct processes in place to extract insights from the available data. In turn, this can inform everything from operational and strategic direction to sustaining business through to an economic recovery.
While many have come to accept that data analytics provides a competitive advantage, there are still challenges to how best to integrate it with existing systems and processes. And with data continually growing inside the organisation, expectations are high that it will provide a ‘silver bullet’ to fix all business challenges.
This sees the C-suite (especially the CIO and CFO) under the spotlight to provide this value from data analysis sooner rather than later. Of course, the reality is that integration challenges will always exist. Even when the business immerses itself in new technology, those solutions date quickly, and newer ones need to be found.
Building a foundation
As with any technology implementation, the success of data analysis is determined by how effective the basics are done to ensure a solid platform to build on. Bringing together data from across the organisation must be an integral step in this process to ensure silos are broken down and insights can be pulled from the likes of finance, marketing, business development, and so on.
This also provides for an environment where data can be viewed in context. Breaking down inter-organisational data boundaries mean analysis can be done on what impact decisions (as well as external factors) can have on the entire business, not just a component of it.
Fortunately, data has become significantly more accessible to a wider variety of employees inside the organisation. Software tools have contributed to a more user-friendly environment where different job functions can pull specific insights relevant to their requirements. This also means there is not such a reliance on data scientists as before.
All of this contributes to an enabling environment where data analysis provides the insight necessary to improve operational efficiency, competitive solution development, and end-user differentiation. Knowing what customers are looking for, how they use the provided solutions, and what their unique requirements are, can all be fulfilled by data analytics.
And that means the difference between a business that is struggling for survival and one that identifies opportunities for growth.