The logic behind digital transformation is that the greater use of technology and data will generate efficiencies, increase productivity and grow revenues. Existing processes will be overhauled, and new ways of working will be identified.
There are a myriad of ways in which digitisation can achieve these business goals and the adoption of intelligent infrastructure can increase the effectiveness of transformation efforts.
The use of technologies, such as intelligent networking infrastructure and cloud-based applications, provides organisations with greater visibility over their IT environment and enables artificial intelligence (AI)-based automation.
Data is the lifeblood of digital transformation and as more devices and systems become connected, more information about an organisation’s technology environment can be collected.
The exponential growth of data is well documented. According to a study by IDC, data generation will reach 163 zettabytes by 2025 – a tenfold increase from 2017 – as consumers and business use of connected devices and data intensive applications increases. In the enterprise world, Gartner predicts that there will be 5.8 billion Internet of Things (IoT) endpoints by 2020.
It’s a cliché that this data explosion is both a challenge and an opportunity for organisations, but it is also a truth. Data growth combined with a diverse range of enterprise applications is placing increasing demands on rigid IT infrastructure that was designed for more predictable workloads. Inefficiencies, downtime, and a failure to meet expectations can undermine any digital transformation initiative.
A more agile approach to infrastructure, coupled with an added layer of intelligence, can help IT departments cope with this changing landscape. The use of cloud-based technologies, software-defined infrastructure (SDI) and Artificial Intelligence (AI) will provide greater insight and visibility. This allows for optimisation and automation that will benefit the entire organisation.
Much of the data generated by businesses will be used to improve service levels and identify efficiencies. As more systems and applications become connected, organisational data will be used to optimise infrastructure itself.
Automation is frequently cited as one of the main benefits of digital transformation, with manufacturers benefiting from the automatic enaction of insights gleaned from customer data or from changes that can be made to the factory floor. But the principles of automation and machine learning are the same for IT.
The combination of intelligent networking platforms and the IoT sees millions of datapoints fed into algorithms that can either make recommendations, such as a new configuration or policy, that can be enacted manually, or take action automatically. The increased adoption of SDI will enhance the effectiveness of these capabilities, while edge computing will allow for optimisation to take place in real time.
For example, mobile phone operators are using Self-Optimising Network (SON) technology to optimise their infrastructure. SON crunches customer call, text and data information to see if there are any software-based decisions that could improve capacity or network quality – such as the remote tilting of antennas.
Intelligent infrastructure could also analyse an organisation’s data to prevent IT problems before they occur, minimising the threat of downtime.
Gartner estimates the average cost of downtime is $5,600 per minute which equates to more than $300,000 an hour. This is of course an average figure that doesn’t take into account individual circumstances or reputational damage, but it illustrates the potential seriousness of an outage. Any interruption to service can seriously damage employee productivity, result in lost sales and incur additional costs sustained from the restoration of IT services, legal fees or compensation.
Intelligent infrastructure combined with a managed IT service like Insight Managed Infrastructure (IMI) can detect data patterns that suggest a failure is imminent and undertake predictive maintenance. Some Device-as-a-Service (DaaS) vendors perform predictive maintenance for endpoints including PCs, smartphones, and Point of Sale (POS) terminals.
Reducing the Burden
If optimisation and maintenance is handled automatically, then the maintenance burden on IT departments is significantly reduced. Digital transformation has elevated the role of IT from one tasked with simply keeping the lights on, to a division that is viewed as a key driver of business change.
However, these additional responsibilities are placing significant pressure on IT departments contending with insufficient or even contracting budgets to fulfil both roles. According to the 2019 Insight Intelligent Technology Index (ITI), 66% of IT departments believe they are being set up to fail as they manage dual roles of maintenance and innovation.
The optimisation and automation promised by intelligent infrastructure can ensure that IT departments are free to focus on innovation projects without compromising maintenance.
Digital transformation will unlock a raft of opportunities for organisations of all sizes, but it’s important that the underlying infrastructure that will power these customer and employee experiences isn’t forgotten.