With political and economic uncertainty likely to affect many aspects of businesses across the globe for the foreseeable future, organisations need enhanced frontline agility, says Chris Norton, managing director, InterSystems UK & Ireland.
Trade tensions, the upheavals caused by extreme weather, and the lingering after-effects of the pandemic are all adding to an already volatile atmosphere. Businesses have had to cope with a seemingly incessant series of interest rate rises in the developed world, while inflation, although abating, has proved to be more stubborn than many central bankers foresaw.
In an age dominated by information, the ability to excel in the face of these pressures requires the ability to look deep inside data and processes to understand exactly what is happening in the moment. Organisations need to predict the changes coming their way, and respond rapidly with maximum benefit.
In every corner of the world, organisations must become far more agile, which requires innovation. They need to be capable of seizing new opportunities as well as predicting how threats will emerge so they can side-step or mitigate them. A survey of senior business leaders across healthcare, financial services, fintechs, supply chain, and education found that 74% view innovation as vital to their organisation’s success, with more than half saying agility is one of the key drivers of innovation. The opportunities continue to surface, but they demand new approaches to data management, and the extraction of insight and value. From top to bottom, organisations must become more data-driven. Frontline executives and team leaders need access to critical data and insights that enable them to make the right decisions very quickly and before their rivals.
Talent shortages and data overloads affect every area of the globe
However, talent shortages and growing data complexities are creating data-related bottlenecks with IT or developer teams, delaying further innovation across business units. Organisations are battling resource constraints and struggling to implement innovative approaches to decision intelligence. More than a third of organisations (35%) cite the skills shortage as the biggest roadblock to success.
The US Department of Labor has predicted an 85 million global shortfall of software engineers by 2030, while consultants McKinsey say the swathe of lay-offs at well-known tech companies has done little to resolve the disconnection between supply and demand for technology skills. The European Commission estimates that by 2030, the shortage of ICT specialists in the EU will reach eight million. More than 60% of EU enterprises that tried to recruit ICT specialists had difficulties in finding the right personnel, with this lack of data skills being almost universal.
This skills shortage is a significant hurdle, given that the volume of useful data available to almost every business is constantly expanding. Organisations around the globe find that as the data they need to analyse keeps increasing, it is filling vast, distinct silos, and there is a lack of data science skills and underlying technology to bring all this information together for effective, value-driving analysis. Without them, it is very difficult to achieve anything that makes the organisation more swift-footed, responsive, and profitable.
Self-service analytics
This may once have seemed like a hopeless position, but this is no longer true. Organisations should not be overwhelmed by the volume of data or frustrated by their lack of expertise. The development of self-service analytics has expanded organisational agility and given every business user the power to make data-driven decisions, regardless of their technical skillset. Advances in data management technology mean non-specialists can now prepare data and ensure they and their colleagues have access to information that is of the right quality, accuracy, integrity, and timeliness.
Automation has reduced the routine and repetitive processes involved in data preparation, while the introduction of innovative data fabric architectures means lines-of-business frontline users can conduct their own queries on live or historical data in any system or silo. No more must staff rely solely on the talents of IT colleagues or data engineers and scientists whose time is highly constrained.
Using this data fabric approach, the data being analysed can stay where it is. There is no need to implement additional systems or undertake a major replacement programme. Frontline decision-makers can quickly obtain answers to the business questions that will deliver the greatest benefit to their work, or that of their team. They can employ business intelligence and data visualisation tools to make complex answers easy to understand. Interactive and multi-dimensional analysis no longer depends on the availability of IT data expertise.
Liberated from much of the routine work and the demands arising from a deluge of business requests, data engineers can devote more time to complex work that has the potential to deliver greater value, such as the creation of new data assets.
New data capabilities for lines-of-business users in the supply chain or financial services
With access to on-demand analytics, frontline staff in decision-making roles find they can adapt to new threats and opportunities much faster. Innovation and agility become embedded in to standard practice. Access to live data and diagnostic, predictive, and prescriptive insights gives supply chain organisations lightning-quick reflexes in the face of disruptions, so they can re-route or resupply. They can adopt alternative strategies that maximise important fulfilment metrics without adversely affecting profitability or efficiency in other areas.
In financial services, self-service analytics tools give front and back-office teams the ability to drill down into live data and ask questions that suddenly become critical. No longer do they have to wait for their data specialist to have time. They can create their own dashboards and reporting screens to meet their unique demands.
For frontline users in asset management, these new capabilities mean they have access to more sources of data and to insights that drive important investment decisions, based on what may be masses of trading data and market information. They can predict what could happen next by conducting analytics on fast-moving transactional data.
Ignoring advances in self-service analytics is inadvisable
The arrival of self-service data and analytics functionalities has opened the door to a new kind of agility and competitiveness. Organisations that lack these capabilities risk falling behind significantly. There is another risk too; they may discover that shadow data silos emerge as their own line-of-business users experiment outside governed environments. Employees who want to see progress, know what is possible, but feel frustrated by their own organisation, may take matters into their own hands. This comes with all the adverse data governance and IT consequences of uncoordinated, unsupervised, DIY approaches.
Yet it is undeniable that as competitors’ frontline teams acquire new capabilities that enable them to make faster, and better decisions that have real business impact, an organisation still working with overflowing data silos will become more sclerotic. Unable to harmonise expanding volumes of data in a timely and effective way that delivers frontline value, it is very difficult to become an agile organisation. But when front-line business users gain new, advanced self-service data and analytics capabilities, their organisation significantly improves its agility, ready to respond with maximum effectiveness to all the challenges of a more volatile world.
The author is Chris Norton, managing director, InterSystems UK & Ireland.
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