Smart interpretation of data is fast becoming a necessity. The onus is now on companies to leverage on this initiative to realise greater productivity.
By AUGUSTINE OMONDI
Various business organisations and small and medium enterprises across the world in various sectors are increasingly approaching the businesses from a customer-centric perspective, amassing infinite quantities of customer intelligence in the process. But harnessing this data deluge has been a huge challenge. Everyone is aware that big data brings excitement to the organisations but again not everyone is aware that big data sometimes fails to deliver the big insights that were hoped for. Rarely do firms tackle this topic. It would be of a massive benefit to identify a correlation that exist between the big data and the overall corporate performance, the kind of capabilities and investments needed, impact at stake and the most vital levers.
Correlation between big data and overall corporate performance
In the global market, businesses, suppliers and customers are creating and consuming vast amounts of information. This flood of data is what we refer to as big data, data deluge or information overload. Big data has created enormous challenges to some organisations that have no clue on how to create value from the data they have. Mesmerizingly, even in the wake of these challenges, executives of these companies have continued asking for more data and with speed which begs the question: are company executives addicted to big data? Is there a correlation between the big data and corporate performance?
Many company executives focus on the key performance indicators (KPIs) to monitor progress of their organisations forgetting to find out a correlation between success attained and specific factors that might have driven that success. This is where they go wrong. Using KPI to monitor say a sales person performance in an insurance company would provide a backward-looking snapshot of a salesperson performance. It would do nothing to help the salesperson or the manager to understand the everyday behaviours that are responsible for the outcome. It would be more interesting and impactful if a manager would take some time to find out which daily activities are correlated with successful outcomes, intervene for employees who are falling behind and encourage employees to adopt best practices to improve sales performance.
This is where analytics come in. It has been the missing link between real- time work behaviours and quarter end lagging indicators. Predicting outcomes and improving productivity would allow companies to course-correct before quarterly results are in. People analytics, an emerging big data technology, draws on aggregated, anonymized data from email, calendar, and other company-specified datasets, to help employees and executives understand how time is invested, and if it’s paying off with increased sales. Simply put, the data would help company executives recognise why some employees are not meeting their targets and how to best coach them towards improvement. In the absence of these data, they cannot provide fact-based coaching toward practices that bolster sales within their own organisations.
Anyone who’s taken a basic statistics class understands that correlation does not equal causation. But correlation can illuminate fascinating relationships between behaviours and outcomes. While the data are promising, we should proceed with prudent optimism. People analytics isn’t a cure-all for poor salespeople, and there’s likely a confluence of behaviours that lead to success in sales.
What analytics can do and always does is to provide companies with unprecedented insight about what successful employees are doing within their organisation that effectively leads to high performance. We can use the data as a basis to coach employees and conduct a split testing around which behaviours seem to have a causal relationship with high performance, versus an associated relationship. Analytics data provide extraordinary visibility into what successful people do and how others can replicate those behaviours. Companies won’t reap the full benefits of a transition to using big data unless they’re able to embrace and manage change effectively.
A study conducted by McKinsey Global Institute shows that 27 per cent of companies have a clearly defined business intelligence and analytics strategy,57 per cent don’t , while 17 per cent don’t know whether they have one or not. My assumption would be that the 73 per cent of these organisations have placed more resources on IT as opposed to analytics. This is an approach that is being applied by the laggards. For the winners, they have taken an integrated approach by realizing that analytics is a strategy rather than a purely IT issue. There is a need for companies to understand that relying on technology alone might not be the answer but making use of the customer information is what will make the difference in terms of quicker decision making and creation of new products for your clients without them asking for them.
Whether termed “strategic analytics,” “business analytics” or “customer analytics,” smart interpretation of consumer data has already become an absolute must, not simply a nice-to-have value driver. From leveraging the converged cloud with intuitive interfaces to prescriptive models that match segments to campaigns, offers, and content using every conceivable channel, analytics is key to maintaining a competitive edge. In view of these developments, one can assume that every company will be performing customer analytics as a matter of course in the near future. The call to action for Chief Executive Officers of laggards will therefore be to diagnose their status quo and catch up as swiftly as possible.
However, truth be told, champions will not be able to rest on their laurels. Since all the players will be in on the game and improving by the minute, champions need to prepare themselves for a pure-play strategy that elevates them to operational excellence, with the lowest costs coupled to the greatest possible benefits. Operationalizing the insight value chain along every link will be the key. Catapulting themselves into the next dimension of integrative data analysis that encompasses the entire ecosystem of industry players will not be easy, but the rewards will far outweigh the effort.