Qlik’s Jesse Cugliotta discusses why data is crucial in the heavy industries.
Industry 4.0, the rise of Internet of Things – the heavy industries of manufacturing, construction, transportation and utilities are becoming ever more connected. Gartner forecasts that 25 billion connected things will be in use by 2021. That means huge amounts of data being produced – information that needs capturing, processing and disseminating in order to extract true value.
Yet to do that requires organisations to have the ability to understand data. In other words, they need to be data literate.
We are seeing the way we work undergoing a major shift, with jobs evolving and adapting rapidly to meet this data driven climate. Indeed, recent research found that 63% of businesses are looking for employees that can demonstrate their ability to use, work with and analyse data.
The opportunity, if they can develop data literacy, is significant – Qlik’s Data Literacy Index (DLI) says that companies that improve their corporate data literacy may benefit from an increase in enterprise value of between three and five percent, which equates to a staggering $324 to $534 million. Workforce data literacy also has a proven correlation with corporate performance, and is known to impact positively on other measures of corporate performance as well – including gross margin, Return-on-Assets, Return-on-Equity and Return-on-Sales.
Yet for businesses operating in heavy industries, that may be too much to ask. Those leaders working in manufacturing, resources and construction, transportation and utilities that participated in a recent survey admitted to lacking confidence in their organisations’ data literacy. In fact, only 59 percent of those surveyed had even heard of data literacy, compared to a cross-industry average of 67 percent. This is despite almost all (97 percent) saying that data is important in how their company makes decisions.
Part of the issue may be the value leaders in heavy industries place on data literacy, or the lack thereof. Despite the constant talk of Industry 4.0 and the increasing use of IoT, less than half of business leaders from the sector believe that data literacy is very relevant to their industry.
It would appear this is unlikely to change soon – just under a third (30 percent) of those surveyed leaders think data literacy is a very important factor when hiring, suggesting that it is not a priority for all.
This might seem like a contradiction – to have smart factories, meters, wind turbines, connected housing, yet limited desire to understand the data that all these innovations generate. One of the current issues is that while leaders recognise the value of connecting production lines, processes and hardware, many are only looking at each part in isolation.
So, for instance, that might mean investing in sensors to monitor heavy goods vehicles for maintenance, and separate technology for tracking location, and not thinking about how the two can work together. In effect, this creates data silos, where the lack of a complete view means limited value can be extracted.
It’s a situation that plays out in the research results, with few leaders expecting employees to be data literate – only 14 percent of heavy industry respondents significantly encourage their workforces to be comfortable with data, and less than a third (32 percent) provide data literacy training. Most tellingly, just a quarter of sector replies said they are willing to pay higher salaries to employees who are data literate.
A lack of data literacy also means that businesses aren’t as comfortable at making decisions that could help with the likes of productivity and staffing. Data-driven decision-making fared badly in our global research, indicating that even if companies do have data literate employees, a lack of universal literacy means that not every business unit has the ability to turn data into useable information as effectively as they could.
That said, there are some areas of data literacy which heavy industry firms are focusing on. While our survey respondents reported a lower usage of data decision making than other sectors in the Index, it outperformed the cross-industry average when it came to data analysis. Thirty seven percent of heavy industry respondents reported that data analysis influences measuring corporate performance and demand forecasting, a noteworthy 11 percent ahead of the average. A deeper dive into the professions that make up heavy industries finds that 73 percent of engineers use data analytics, well ahead of banking (54 percent), the commercial sector (56 percent) or services (58 percent).
Is this light at the end of the tunnel, or merely a silver lining? With data analytics often the first step in cohesive data comprehension, it is hoped it would suggest the former over the latter. As with any industry, there are examples of manufacturers, utilities companies and logistics businesses understanding the power of data or rejecting it completely. Most sit somewhere in the middle, perhaps wrestling with contrasts and contradictions within their own organisation.
While this data suggests at least a good grounding of data literacy knowledge in the heavy industries sector, it’s important for businesses to continue investing more in this area. The world is shifting rapidly around the Fourth Industrial Revolution and many of the new jobs that will appear over the next decade will have little resemblance to the roles of today. As such, organisations and individuals should be doing all they can to prepare themselves to succeed in this rapidly changing world. Data literacy is an increasingly important currency in this new landscape, and has the ability to make sure the current and next generation of workers are ‘future-proofed’ against these seismic changes.
What is clear is that investment is being made in technology to unlock new opportunities, yet in order to fully understand and reap the associated benefits, companies need a requisite grasp of data literacy. Businesses in the heavy industries sector that fail to do so, run the risk of losing valuable ground on competitors and will struggle to thrive in this data-driven era.