In a short time, humanity has come a long way. Since the creation of the printed word 650 years ago, humans have moved from being isolated clans to a cohesive society, founded on shared information.

Of course, when we talk about connectivity today we’re talking about technology - over 30 years we’ve developed 5 generations of cellular connectivity, with each generation offering significantly improved communication possibilities over the previous version. We’ve gone from voice calls enabled by 1G to being able to watch HD video with 4G. Today’s connectivity enables multiple possibilities to become proactive when making business decisions.

Time and again it’s said that 5G is a game changer, enabling connected vehicles, production lines, logistics, and smart cities and ports with greatly improved capacity and latency – basically how long it takes for data to travel between its source and destination. There are various predictions for these applications, but some have cited that in urban areas there could be as many as one million 5G connected devices per square km by 2025.

Reimagining telecoms is about reimagining the possibilities of this connectivity and the resulting data. The difference with telecoms is that the data can belong to things as opposed to people.

The big tech companies have democratised information to a large extent and this has helped them to gain a significant competitive advantage. Alphabet, for example, has a revenue of $150 billion according to CNBC, with 80% of this revenue coming from targeted advertising related to data collected from customers who use their search facilities.

So how can telcos realise their aspirations to similarly monetise their data? Traditionally they’ve been focused on leveraging customer data derived from their customer management systems, however the real opportunity lies in making better use of the data generated and consumed on devices to create intelligence and insights.

Although many believe that the big issue with 5G and IoT is standardisation and data governance, with many believing that metatagging is important allowing for multiple and variety of devices to be plugged into IoT platforms, it’s my belief that they’re mistaken, and that this holds companies back when it comes to dealing with fundamental challenges when we look at the wider data or ‘information’ of things. Increasingly, devices will be generators of data and consumers of data, so the regulation and the usual challenges around data governance won’t apply. The real issue with the connectivity we enjoy today is that devices have become both generators and consumers of data, making it difficult to identify exactly who owns that network’s data and intelligence. This raises questions around the exchange of such data, and how these interactions and relationships might help enhance business value even in the face of such challenges.

Telcos, therefore, need to reach agreements with their clients and consumers to enable the data to be aggregated and built into ‘wisdoms’ in such a way that insights can be created and reused in different contexts. For example, in the context of smart journey planning or smart parking solutions, the derived data from locations, traffic hotspots, accident information and the capacity of car parks could help with providing intelligence to inform traffic light ecosystems, providing better traffic flow and intelligence to help drivers with real time satellite navigation intelligence to help speed up their journeys. Furthermore, classification, clustering and other innovative data techniques can be applied to help in this respect.

In addition, virtualisation models - where virtual resources are created, such as servers, desktops, networks etc - need to be designed to achieve greater shared value. An example of this is ‘digital twins’, where a virtual resource serves as the real-time digital counterpart of a physical object or process. This is particularly relevant as society becomes increasingly virtualised through the delivery of anonymised personas and avatars in cyberspace. Data sets and ‘big data’ will also grow exponentially, with Edge-based AI and analytics offering automation in specific areas.

When it comes to building a data-driven business strategy, the key considerations are around building trust so that the data is able to be used in the first place, and ensuring the data being collected (and acted upon) is relevant to provide a return on investment (ROI) from the activity.

In addition, there are some key aspects that need consideration when managing and realising the value of data which apply to building trust, relevance, return on investment, and building a strategy. Specifically when democratising data, the below aspects should be considered:

  • First off is the data dimensions, i.e. information that defines the characteristics of the data – for example, if we were talking about defining a person, it would be elements such as height, weight and unique identifiers.
  • Data decentralisation - increasingly, data needs to be held in diverse and varied storage systems that require permissionless access to eliminate the need for a super-administrator. There’s just too much data for this to be effective as a centralised role, with the systemic dangers too great for any one system to keep control. One approach to controlling this might be through the use of blockchain or distributed ledger technology.
  • Allowing for data monetisation through a digital handshake - providing a market-driven ‘consent-based’ agreement between protocols that adheres to the GDPR regulations and other privacy frameworks will be fundamental


In summary, the promise of IoT and 5G is a wake-up call to the industry to reimagine how telecoms providers can increase income from their business in areas other than connectivity. It is very likely that competition will increase and there will be new providers who will eat away at the space if the telcos don’t, such as big tech companies, satellite operators and cable providers. The battleground is around ideas and innovation for data and intelligence as well as IP-related agreements. IoT and 5G offer the promise of new vectors for those wishing to add business value but the right structures and right partnerships, complemented by a diverse set of skills, is what’s needed.

At Capita we understand the challenges facing data-driven businesses, including the need for unlocking the potential of AI and data. We’ve created education pieces, such as the AI periodic table which shows the main components in the value chain whilst determining those clusters of data that add value and avoiding data becoming useless or siloed.

Tirath recently co-authored a book together with Doug Brown, Head of Artificial Intelligence and Analytics Guild at Capita, titled Data Alchemy: The Genesis of Business Value.

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Written by

Al Murray

Tirath Virdee

Director for Artificial Intelligence at Capita

He has been involved with the national data strategy and is a permanent member of the All-Party Parliamentary committees for AI and Blockchain. Tirath works with one of the best teams in the country that solves data. For Tirath value is in the data that the subject consumes and produces and the value it brings to the network. As one removes the jargon of technology stacks, one can realise the true vectors that enable us to reimagine our businesses.

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