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Understanding your data: How to drive insight from raw numbers
Fri, 31st Aug 2018
FYI, this story is more than a year old

Software is now at the heart of everything a business does. From important SaaS functions in the cloud to an essential ERP solution, software is becoming a crucial fuel for business performance and revenue growth while end users are demanding more control over their devices and data, including flexibility in how they use and pay for devices. Whether it's everything-as-a-service, outcome contracts, software licensing, subscription modelling or simply pay-as-you-go, the ways end users interact with vendors are changing.

The combination of software and connectivity allows manufacturers access to a new, powerful asset: data. This can provide great value. With this, they are able to better understand the value that they offer, and how their solutions are being used. Data opens up new insights such as the most popular features, times of usage and features that aren't being adopted.

The trend toward adding value through software – and increased access to data through connectivity – seems here to stay. An overwhelming majority (85%) of organisations that manufacturer software-enabled hardware agree that data is the future of their business, according to our ‘How Software is Powering the Hardware Renaissance' report. However, nearly half of businesses (47%) don't have the skills to analyse the data they have or will collect. Businesses are also struggling to hire staff with the right skills to fill these gaps and turn the data they hold into insights.

Opening the data door

Data skills alone are not enough when looking to hire, businesses must look to those who have skills in data management, data analysis and data security:

  • Data management – Accessing data is one thing, successfully managing the data that is coming in and out of the business is another. Expertise in data management is crucial in order to take advantage of that data.  Data management is effectively the umbrella under which all other data disciplines sit and requires organisational, technical and analytical skills.
  • Data analysis – Once the data has been collected and stored, it needs to be correctly sifted through, interpreted and analysed. In order to be successful in this area, they must be able to analyse, model and interpret data, and use those insights to make effective business decisions that will benefit the company. It means employees must be good at problem-solving and have great organisational and research skills.
  • Data security – Companies need to realise that the data they hold – and the insights it leads to – has the potential to separate them from their competitors. As such, it's inevitably going to be a target for hackers, looking to seize that data for their own gain. It is imperative that businesses hire someone with the skills to ensure that data is protected at its core through security measures like encryption and multi-factor authentication is essential.

Retraining and the upskilling current staff is one route to closing the gap. As hardware manufacturers transition to a more software-based approach, seven out of 10 (67%) of them agree there will be fewer hardware engineering roles available within 10 years. These employees could be good candidates for reskilling.

The good news is six out of 10 (64%) have already started to do this, with more expected to follow suit. With these staff already up to speed on internal processes and immersed in its culture, the speed at which they can be inducted into new roles can help businesses avoid missing a beat.

A human-automation future approach

With manufacturing gearing up for a seismic technological shift, the ability for connected devices to communicate with one another and automate functions will be critical to driving the industry forward. Yet, this automation doesn't mean the end for human jobs. In fact, a recent study by Deloitte found that despite 800,000 low-skilled jobs being eliminated as the result of AI and other automation technologies, that over 3.5million new high-skilled jobs were created, showing the positive balance of investing in these areas.

Despite the growth in automation in the coming years, businesses will still need the skills that humans bring. It's our creativity and problem-solving abilities that enable us to manage and analyse the data and generate those key insights that will shape strategy for years to come.

The businesses that succeed in the future will be those that can find the right human-automation balance, retrain and upskill their staff effectively, and bring in expertise from outside quickly. The era of automation is near, and businesses must look to developing the correct skills to take advantage and move forward.