By: Sean Taylor Director at Insight Consulting
Most C-suite executives recognise that their organisations could do more to transform their data supply chains, allowing them to extract more value and insight from their internal data assets. A data strategy cannot exist outside the business strategy. In other words, to achieve business goals in our evolving and highly competitive world, organisations would do well to choose innovative partners, stay abreast of data trends and evolve to become a genuine data-driven entity, that’s data literate.
Data harvesting, usage and analytics is evolving at breakneck speed, and there are a few data trends that all businesses should be planning for. However, even before plotting a data strategy, businesses should understand that security and governance spans the length and breadth of data access, consumption and value creation. This is where the choice of platforms and partners is crucial. This, in turn, talks to a theme that will be echoed in most of the trends below: there is no space for silos in a modern data business. Strategy, security, governance, technology, personnel - there must be harmonious planning and communication between all functions.
Here are some important data trends in 2022 for C-suites to consider:
The full data value chain
It is important to appreciate the concept of a full data value chain. Managing data with this mindset is really a methodology of accessing, consuming and creating value from data. In order to achieve this you’d naturally need to go through the process of finding out where you are now and where you want to be, and then plugging the gaps to get you there. Those gaps may be in multiple, disparate areas of your data supply chain and having a partner that can fulfill that full data value chain, or assist in taking you forward in any step along that value chain, becomes essential for a data company to survive into the future.
The chief data and analytics officer (CDAO)
It is important to acknowledge the emerging role of the chief data and analytics officer (CDAO). This person’s role is cross-functional and increasingly vital as they innovate communication between different functional areas in the businesses, including IT. Previously, for example, software development was in a silo by itself, and data analytics was in another silo, and so on. The CDAO’s role is to break down these walls to completely open up that data supply chain.
New techniques and architectures
On an almost ongoing basis we are seeing the emergence of new techniques and architectures involved with the collecting, processing and managing of data. This is certainly something we at Insight Consulting are aware of in the data integration space - there’s a great deal of app-generated data nowadays and this is important as it marks a sharp change from before, where core analytics was highly structured and database driven. This is shifting. If you really want to capitalise on your data value chain, you must start bringing in data from more unstructured sources.
Micro and automated capture applications
The trend of micro and automated capture applications has come about to optimise the way data is ingested into an organisation to improve governance and chase a quicker time to value. Specifically in the data analytics space, we’re seeing an increase in the integration of artificial intelligence (AI) and machine learning to deliver highly focused and more contextualised dashboards. We are seeing a move away from self-service, where users would analyse the data themselves. This is largely driven just by the incredible increase in data volumes. It's just not practical or possible for humans to slice through the sheer volume of information as efficiently as technology.
As a result, we see analysis moving into the automated space where AI has managed to codify the trends and exceptions, and pushes those out to more contextualised dashboards. Perhaps the most exciting thing here is that there is a focus on micro insights for specific business users, giving them actionable insights that they can actually do something with that would benefit the business.
Machine learning and other AI technologies are revolutionising big data analytics. AI's ability to ingest and analyse massive amounts of structured and unstructured data is being used by companies to optimise and improve business operations. In the pursuit of getting actionable insights from analytics into hands that can take appropriate action, there needs to be a viable way of disseminating this information. The era of self-service is making way for the era of chatbots, developed specifically for this purpose. Today it’s possible to have a situation where someone is going about their work and the bot brings to their attention important exceptions or trends related to their function in the business.
As is evident from the trends listed, technology is playing an increasingly important role in data analytics. By removing the time-intensive burden, technology elevates the human role in a business. With increased business understanding, delivered efficiently and quickly, managers can focus on strategic thinking and decision-making. To achieve this state, businesses would do well to partner with organisations that appreciate, and accommodate for, the full data value chain.