Scaling private cellular and edge: How to avoid POC and pilot purgatory

Evaluating the opportunities with private cellular and edge

The majority of enterprises today are still at the early stages of understanding the potential benefits of private cellular networking and edge computing in delivering enhanced business outcomes, but the interest is evident. Within private cellular for example, we have seen significant traction and uptake globally during 2020 and 2021, partially driven by increased availability and routes to spectrum due to localised spectrum licensing models across different markets (see this report). This has resulted in several trials and engagements with large companies such as Bosch, Ford, Rio Tinto, Heathrow Airport and more.

However, despite the rising interest, enterprises often encounter challenges with a lack of internal stakeholder alignment or the inability to find the right stakeholder to be accountable and own the deployment. Furthermore, many enterprises feel they lack the expertise to deploy and manage private networking and/or edge solutions. In some cases, enterprises have also cited a lack of maturity in the device and solution ecosystem, for example with lack of supported (or industry-grade) devices which have a 5G/LTE/CBRS capability embedded in them, or a significant inertia in the installed base around other connectivity solutions (e.g. Wi-Fi). Therefore, despite the value and business outcomes that private cellular and edge compute can unlock for enterprises, the opportunity is rarely clear-cut.

Our research is based on findings and analysis from a global interview programme with 20 enterprises in sectors that are ahead in exploring private cellular and edge computing, primarily in the industrial verticals, as well as telecoms operators and solutions providers within the private cellular and edge computing ecosystem.

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Telcos see private cellular and edge as two peas in a pod…

Telecoms operators see private cellular and edge computing as part of a larger revenue opportunity beyond fixed and public cellular. It is an opportunity for telcos to move from being seen as horizontal players providing increasingly commoditised connectivity services, to more vertical players that address value-adding industry-specific use cases. Private cellular and edge compute can be seen as components of a wider innovative and holistic end-to-end solution for enterprises, and part of the telcos’ ambition to become strategic partners or trusted advisors to customers.

We define a private cellular network as a dedicated local on-premises network, designed to cover a geographically-constrained area or site such as a production plant, a warehouse or a mine. It uses dedicated spectrum, which can be owned by the enterprise or leased from a telco operator or third party, and has dedicated operating functions that can run on the enterprise’s own dedicated or shared edge compute infrastructure. Private cellular networking is expected to play a key role in future wireless technology for enterprise on-premises connectivity. Private cellular networks can be configured specifically to an individual enterprise’s requirements to meet certain needs around reliability, throughput, latency etc. to enable vertical-specific use cases in a combined way that other alternatives have struggled to before. Although there are early instances of private networks going back to 2G GSM-R in the railway sector, for the purpose of this report, we focus on private cellular networks that leverage 4G LTE (Long Term Evolution) or 5G mobile technology.

Figure 1: Private cellular combines the benefits of fixed and wireless in a tailored way

benefits of private cellular

Source: STL Partners

Edge compute is about bringing the compute, storage and processing capabilities and power of cloud closer to the end-user or end-device (i.e. the source of data) by locating workloads on distributed physical infrastructure. It combines the key benefits of local compute, such as low latency, data localisation and reduced backhaul costs, with the benefits of cloud compute, namely scalability, flexibility, and cloud native operating models.

Figure 2: Edge computing combines local and cloud compute benefits to end-users

benefits of edge computing

Source: STL Partners

Within the telecoms industry, private cellular and edge computing are often considered two closely interlinked technologies that come hand-in-hand. Our previous report, Navigating the private cellular maze: when, where and how, explored the different private cellular capabilities that enterprises are looking to leverage, and our findings showed that security, reliability and control were cited as the most important benefits of private cellular. In many ways, edge compute also addresses these needs. Both are means of delivering ultra-low latency, security, reliability and high-throughput real time analytics, but in different ways.

…but this is not necessarily the case with enterprises

Although the telecoms industry often views edge computing and private cellular in the same vein, this is not always the case from the enterprise perspective. Not only do the majority of enterprises approach edge computing and private cellular as separate technologies, addressing separate needs, many are still at the early stages of understanding what they are.

There is oftentimes also a different interpretations and confusion of terminology when it comes to private cellular and edge compute. For example, in our interviews, a few enterprises describe traditional on-premises compute with local dedicated compute facilities within an operating site (e.g. a server room) as a flavour of edge compute. We argue that the key difference between traditional on-premises compute and on-premises edge compute is that with the latter, the applications and underlying infrastructure are both more cloud-like. Applications that leverage edge compute also use cloud-like technologies and processes (such as continuous integration and continuous delivery, or CI/CD in short) and the edge infrastructure uses containers or virtual machines and can be remotely managed (rather than being monolithic).

The same applies when it comes to private cellular networking, where the term ‘private network’ is used differently by certain individuals to refer to virtual private networks (VPNs) as opposed to the dedicated local on-premises network we have defined above. In addition, when it comes to private 5G, there is also confusion as to the difference between better in-building coverage of public 5G (i.e. the macro network) versus a private 5G network, for a manufacturing plant for example. This will only be further complicated by the upswing of network slicing, which can sometimes (incorrectly) be marketed as a private network.

Furthermore, for enterprises that are more familiar with the concepts, many are still looking to better understand the business value and outcomes that private LTE/5G and edge compute can bring, and what they can enable for their businesses.

 

Table of Contents

  • Executive Summary
  • Introduction
    • Evaluating the opportunities with private cellular and edge
    • Telcos see private cellular and edge as two peas in a pod…
    • …but this is not necessarily the case with enterprises
    • Most private cellular or edge trials or PoCs have yet to scale
  • Edge and private cellular as different tracks
    • Enterprises that understand private cellular don’t always understand edge (and vice versa)
    • Edge and private cellular are pursued as distinct initiatives
  • Breaking free from PoC purgatory
    • Lack of stakeholder alignment
    • Ecosystem inertia
    • Unable to build the business case
  • Addressing different deployment pathways
    • Tactical solutions versus strategic transformations
    • Find trigger points as key opportunities for scaling
    • Readiness of solutions: Speed and ease of deployment
  • Recommendations for enterprises
  • Recommendations for telco operators
  • Recommendations for others
    • Application providers, device manufacturers and OEMs
    • Regulators

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Telco A3: Skilling up for the long term

Telcos must master automation, analytics and AI (A3) skills to remain competitive

A3 will permeate all aspects of telcos’ and their customers’ operations, improving efficiency, customer experience, and the speed of innovation. Therefore, whether a telecoms operator is focused on its core connectivity business, or seeking to build new value beyond connectivity, developing widespread understanding of value of A3 and disseminating fundamental automation and AI skills across the organisation should be a core strategic goal. Our surveys on industry priorities suggest that operators recognise this need, and automation and AI are correspondingly rising up the agenda.

Expected technology priority change by organisation type, May 2020

technology investment priorities telecoms May 2020

*Updated January 2021 survey results will be published soon. Source: STL Partners survey, 222 respondents.

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Key findings on operators’ A3 strategies

Based on deep dive interviews with 8 telcos, as well as insights from 8 more telcos gathered from previous research programmes.

  • Less advanced telcos are creating a set of basic structures and procedures, as well as beginning to develop a single view of the customer
  • Having a single version of the truth appears to be an ongoing issue for all – alongside continued work on data quality
  • As full end-to-end automation is not a realistic goal for the next few years, interviewees were seeking to prioritise the right journeys to be automated in the short term
  • Reskilling and education of staff was an area of importance for many but not all
  • Just one company had less ambitious data-related aims due to the specialist nature of their services and smaller size of the company – saying that they worked with data on an as-needed basis and had no plans to develop dedicated data science headcount

Preparing for the future: There are four areas where A3 will impact telcos’ businesses

four A3 areas impacting telcos

Source: Charlotte Patrick Consult, STL Partners

In this report we outline the skills and capabilities telcos will need in order to navigate these changes. We break out these skills into four layers:

  1. The basic skillset: What operators need to remain competitive over the short term
  2. The next 5 years: The skills virtually all telcos will need to build or acquire to remain competitive in the medium term (exceptions include small or specialist telcos, or those in less competitive markets)
  3. The next 10 years: The skills and organisational changes telcos will need to achieve within a 10 year timeframe to remain competitive in the long term
  4. Beyond connectivity (5–10 year horizon): This includes A3 skills that telcos will need to be successful strategic partners for customers and suppliers, and to thrive in ecosystem business models. These will be essential for telcos seeking to play a coordination role in IoT, edge, or industry ecosystems.

Table of contents

  • Executive Summary
  • Telcos’ current strategic direction
    • Deep dive into 8 operator strategies
    • Overview of 8 more operator strategies
  • How A3 technologies are evolving
    • Deep dive into 40 A3 applications that will impact telcos’ businesses
    • Internal capabilities
    • Customer requirements
    • Technology changes
    • Organisational change
  • A timeline of telco A3 skills evolution
    • The basic skillset
    • The next 5 years
    • The next 10 years
    • Beyond connectivity

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Digital twins: A catalyst of disruption in the Coordination Age

Digital twins and the Coordination Age

Digital twins are an enabler of the Coordination Age, in which a global need to improve the efficiency of resource use, combined with supply-side technologies like the Internet of Things (IoT), 5G and AI, is driving a revolutionary change in the way that economies work.

In this change, the fundamental mechanism needed is coordination – the organisation of multiple parties and assets to deliver a desired end-goal. Examples of this need can be found in all sectors of the economy and all areas of life, such as healthcare, manufacturing, the smart home, smart transport, etc.

To make this happen in practice a number of practical challenges need to be addressed:

  • Physical and digital assets need to be able to work together more easily
  • Authorised users need better real-time remote insight on and control of distributed assets
  • Certain things and processes need to be able to act with greater autonomy (albeit within clear rules)
  • More realistic and reliable models/simulations are needed to test and evaluate different solutions and scenarios

Digital twins are a means towards all these ends, providing a mechanism whereby processes and things can become interoperable and intelligent on demand to authorised users.

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What is a digital twin?

A digital twin is a digital representation of an existing physical or digital entity:

  • Examples of digital twins of physical entities include twins of simple sensors (such as a temperature sensor), machine components (such as a fan in a motor), a sub-system within a motor (such as a cooling system), the entire motor, or the whole vehicle containing the motor
  • Examples of digital twins of digital entities include digital twins of data, a digital process (such as an order process or an automation protocol), or an entire digital business value network (such as a centralised data warehouse).

Digital twinning is a method of designing information systems that enables:

  • First visualisation, then dynamic control and emulation/simulation of assets. This can be ‘offline’ from the actual asset in the sense of a model to predict behaviours in different scenarios, or in real-time as a means to control and monitor operations.
  • A more efficient way to manage large volumes of data, where instead of collecting ‘data lakes’ storing every data point, data is organised into more manageable datasets capturing only meaningful events. This can reduce the need for data storage by up to 90%, which can be highly significant. An aircraft’s jet engine can generate Terabytes of data in a few hours of operation, for example.

Customers often arrive at the need for digital twins with one or other of these needs in mind, and over time end up utilising both.

Archetypal customers are:

  • Organisations that want to share data and create value from numerous sensors and devices, such as weather stations, and connect consumer devices (e.g. washing machines, doorbells, cookers) to consumer / household app dashboards.
  • Organisations that want to make better use of complex assets by using the data they generate to help them operate more efficiently. Examples of such assets include large buildings, trains, jet engines, manufacturing processes, etc. The first step in this process is to organise the data so that it can be used.

The process may ultimately evolve to the point where the organisation possesses a highly sophisticated twin of the entire asset made with information from many component twins from multiple sensors and sources. The overall twin may comprise both historical data of past behaviour, and live real-time data from the thing.

Figure 1: Example of a composite digital twinComposite Digital Twin Example

Source: STL Partners

STL Partners sees digital twins as a key building block of the Internet for Things, and thereby part of the DNA of the Coordination Age in the way that websites and URLs are part of the DNA for the Information Age.

As well as these wider implications, they have potential applications within telcos, and for their customers and partners.

Digital twins: A catalyst of disruption in the Coordination Age explores why telecoms operators need to understand digital twins and their application. The report then sets out how operators and vendors can best take advantage of digital twins.

Table of contents

  • Executive Summary
  • Introduction
    • Digital twins and the Coordination Age
    • What is a digital twin?
  • What do digital twins do?
    • How is a digital twin different from a simulation?
    • Why else are digital twins exciting?
    • So where is the money?
    • What are the challenges?
    • The evolving impact of digital twins
  • Digital twins for telcos
    • Potential internal applications
    • Speaking customers’ language
    • Telcos as providers of digital twins
  • Dating services for digital twins
    • Civil engineering: Making all the pieces work together in real life

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The IoT is dead: Long live the I4T – the Internet for Things

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Introduction

The Internet for Things and the Coordination Age

In our recent research report The Coordination Age: A third age of telecoms, STL Partners described how the global economy is moving into a new age: the Coordination Age.

This is driven by a global need to improve the efficiency of resource utilisation, arising from a combination of developments in both demand and supply. In terms of demand, there are pressing needs from all customers to make less do more. On the supply side, technologies like AI, automation, ‘digitisation’, NFV/SDN, and potentially 5G, provide a smarter and more flexible way to do things.

The consequence is that coordination is the job that needs to be done across many market areas. People, things and information need to be brought together at the right time and in the right place to deliver the desired outcome.

Examples include:

  • Smart home: devices, sensors, appliances and applications created by many different companies need to be coordinated into an easy-to-manage solution for consumers (see our latest report Can telcos create a compelling smart home?)
  • Healthcare: where clinicians, patients, treatments, resources and information need to be coordinated for successful healthcare outcomes (see Telcos in health – Part 1: Where is the opportunity? and Part 2: How to crack the healthcare opportunity)
  • Transport: coordination is needed to manage transport flows for both public and private transportation, to ensure the best use of available resources and where to direct investment most effectively
  • Logistics: to manage the distribution and delivery of stock and produced goods across highly complex, international supply chains
  • Industry: to ensure that manufacturing and supply-chain processes deliver, assemble and process goods and materials efficiently

The best description we’ve come up with for the common need across these areas is “to make our world run better”. It’s not a generic do-gooding mission, it’s about improving what people and companies get for their time, money, effort and attention.

It’s an over-arching principle (or meta-trend) that makes sense of, and gives direction to, the many technology led ideas like “Internet of Things”, “Industry 4.0”, and others.

But … so what?

It matters because to have a winning strategy first requires a superior (or at least appropriate) mental grasp of the environment, or frame of reference, for that strategy.

Put another way, if you don’t understand how the new game is being played, how can you possibly win?

Telcos frequently missed this trick in the previous 30-year transition into the Information Age.

Figure 1: The three ages of telecoms / ICT

Source: STL Partners

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Over the last 30 years, telcos have continued to think, talk and act like network builders. Consequently, telcos did well out of the broadband and mobile data revolution, but they largely missed out on the services that make use of the raw connectivity and turn it into something more useful.

There are numerous examples of changes the Information Age brought to communications, information discovery, and commerce. These new ways of doing things have ultimately been dominated by other players, like Google, Facebook, Apple, Alibaba and Amazon.

Sometimes, when telcos spotted those opportunities, they missed out because they applied old-style business model approaches in the new world. For example, they often tried to make payments and early information products walled gardens and/or failed to grasp the need to collaborate with others to create a proposition with sufficient scale in practice (e.g. see Apple Pay & Weve Fail: A Wake Up Call).

We discuss the reasons why telcos missed opportunities in more depth in our report How the coordination age changes the game.

Now that growth is reaching the end of its cycle in communications (see Figure 2) telcos have a simple choice: stay as a pure connectivity player in a flat or declining market or develop new service propositions in addition.

Figure 2: The well-worn path of slowing telecoms growth

Source: STL Partners

Whichever route they choose (connectivity only, or connectivity plus services), to succeed and grow going forward, telcos need to rethink their purpose and role in the economy.

How does an “Internet for Things” fit with this?

From about 1990 onwards, the internet was the catalyst for change and growth in the Information Age. By making a huge trove of new information – the World Wide Web – accessible and discoverable, and enabling the delivery of data at volume, it ultimately unlocked new business models, huge disruption, and digital transformation across the entire global economy.

To move into the next age – the Coordination Age – a similar concept and mechanism is needed to be able to discover and access connected things[1].

What’s wrong with the Internet of Things?

There’s a catch with what is currently called the ‘Internet of Things’: it isn’t an internet. It isn’t even a continuous network, and as such is severely limited in its capacity to grow, evolve in intelligence and capability, and deliver the benefits sought.

The Internet of Things (IoT) originated as concept around the turn of the century and has been widely discussed since the early 2010s. Over that time many thousands of ‘smart devices’ and machine to machine (M2M) applications have been developed, creating efficiencies and enhancing functionality in industries as diverse as agriculture, logistics, transportation and medicine. Such applications continue to increase and are often described as ‘the IoT’.

However, most current applications are in reality closed (and private) command and control solutions using standalone technology to limited ends – typically to enhance existing industrial, business or lifestyle functions – such as crop-watering applications that only turn on when the ground is dry, or lifestyle apps like Nest that allow remote control of household functions.

In fact, most of what is commonly referred to as ‘IoT’ is simply an effective use of ICT, contributing to a growing world of connected things – but not constituting ‘an internet’, which is a searchable network of networks that allows users to find and connect to any end-point for which they have appropriate access[2].

There’s a second problem. What’s really needed is not just an Internet of Things, but an “Internet for Things”. Interestingly, in one of the first mentions of the concept, that is precisely what it was called.

“We need an internet for things, a standardized way for computers to understand the real world,”

Kevin Ashton, Auto ID Center at MIT from 1999[3]

The reason STL Partners thinks an Internet for Things (I4T) is a more useful concept today, is that to make some of the most complex and dynamic applications of the Coordination Age work, “things”, including not just sensors but also IT systems, will need to be able to find and communicate with each other relatively autonomously.

The essential components of an Internet for Things

A true Internet for Things, would be much more open than most current IoT systems, and would:

  • Allow discovery of previously unknown sources (e.g. through a search engine), and interactions between communities of things within public or private domains.
  • Allow ‘things’ (including IT processes and software as well as devices) to discover each other within certain predefined rules or protocols, rather than either being given carte blanche to talk with any strange device, or being firmly controlled by a single, central authority.
  • Contain data that is published, searchable, and accessible to anyone – or anything – with the appropriate security access. It would bring data from machines, sensors and other intelligent things into the sharing economy and semi-public domain.

It could also open the door to much more radical initiatives that would combine data from multiple sources to deliver outcomes as yet unconceived of – perhaps triggering further revolutions in terms of efficiency, productivity and innovation.

So why isn’t there an Internet for Things that works more like the world-wide web, but in a machine-based context?

Many companies implicitly recognise the limitations of today’s IoT and are working on solutions to overcome them, some of which are covered in this report, while others will be examined in upcoming reports on Digital Twins and the Industrial Internet of Things (IIoT). This report details further what an Internet for Things is, how it differs from what is described as the Internet of Things, its benefits, and some of the steps that have so far been taken towards it.

What is the Internet for Things (I4T)?

How is an Internet for Things different to an Internet of Things?

Before considering what it would take to create an Internet for Things, it is useful to understand what is currently meant by the expression the “Internet of Things” (IoT).

First, what is a “thing”?

The classic concept of an IoT “thing” is a sensor, or a connected device like a doorbell or machine in a factory. In STL Partners’ view this definition is too limited for the range of real world applications, and the “thing” being connected may be, for example:

  • a bit of data from a single sensor (e.g. the temperature measured by a given sensor, on an aircraft, at a specific time)
  • an aggregated result from a set of sensors (e.g. the average temperature near to a runway in an airport)
  • an industrial process (e.g. a status check on the maintenance needs on an aircraft’s tyres)
  • a consumer process (e.g. an app predicting the likely time of arrival of a flight).

Figure 3: Some examples of what a “thing” can be in the I4T

Examples of things in the I4T

All of these are effectively “things” and their operators may need or wish to share or access this data at any time.

The Internet of Things

Most simple definitions of the IoT describe the connection across the internet of computing devices embedded in everyday devices and machines, such as sensors and actuators, enabling them to send and receive data, be monitored, adjusted, switched on and off and so on.

This describes something that is more like conventional point-to-point or client/server communications than the Internet with which most people are familiar via the world-wide web. The Internet is a relatively open space, in which participants and resources can be identified in various searchable ways – through IP addresses, email addresses, URLs etc. – and located and engaged with.

The openness of the world-wide web makes the volume and nature of possible connections between IP-enabled entities almost infinite. The interactivity between connected things in the IoT, on the other hand, is generally much more limited. It might be better described currently as a world of partially connected things.

What is an “Internet for Things” (I4T)?

STL’s definition of an ‘Internet for Things’ is as follows:

The Internet for Things (I4T) is an open network of participatory, connected devices, objects, processes and entities. I4T entities can be located and interacted with according to their assigned security and privacy settings.

Advantages – what are the benefits of the “Internet for Things”?

An Internet for Things would not just be a collection of smart devices. It would be a digital enabling fabric for wholly new functionality, of potentially great benefit to individuals, enterprises and our environment.

    • An Internet for Things would allow data to be combined and enriched in previously inconceivable ways – mashing up intelligence from different and seemingly unconnected sources for informational, security and commercial purposes.
    • It would enable more meaningful machine to machine conversations. One device might offer enhanced functionality by deriving important contextual information from other communicable entities or devices in its environment.
    • To take a simple example, an in-building climate controller might offer more accurate control based on data taken from security devices, if it could combine data from sources within its network, such as security devices and thermostats, with external sources such as personal smartphones and smart watches, to determine which parts of the building should be heated/cooled, or local weather forecasts, in order to adjust settings in anticipation of changing temperatures.
    • It would trigger a leap in the volume and quality of intelligence available to individuals and agencies. All kinds of “things” – buildings, vehicles, infrastructure elements, people – become data points and data sources, some static, some mobile, all contributing to a vast, searchable pool of crowd-sourced information. This could be mashed and downloaded on demand to create new intelligence for users working in areas unrelated to the source data – e.g. climate data being a driver for predicting cinema attendance figures, in turn used to review film release dates, trigger ice-cream orders and so on.
    • The potential of the Internet for Things is emerging just as the world is facing massive challenges in terms of the use of its resources as we’ve outlined in The Coordination Age: A Third Age for telecoms. These resources and issues range from industrial productivity, climate change, water shortages, major weather events, the move to renewable sources of energy, air pollution and garbage disposal, to name only a few.

Contents of the I4T report:

  • Executive Summary
  • Introduction
  • Credits
  • The Internet for Things and the Coordination Age
  • How does an “Internet for Things” fit with this?
  • What’s wrong with the Internet of Things?
  • The essential components of an Internet for Things
  • What is the Internet for Things (I4T)?
  • How is an Internet for Things different to an Internet of Things?
  • Advantages – what can the “Internet for Things” offer?
  • What problems does the I4T solve?
  • Problem 1: The use case paradox
  • Problem 2: No one really wants to be coordinated by someone else
  • Problem 3: A classic case of warehouse interruptus
  • Two approaches to creating the I4T…so far
  • Interoperability forums
  • Dating services for digital twins
  • Civil engineering: Making all the pieces work together in real life
  • Conclusions: It’s a tough job – but somebody’s got to do it

Figures:

  1. The three ages of telecoms / ICT
  2. The well-worn path of slowing telecoms growth
  3. Some examples of what a “thing” can be
  4. Players in the logistics ecosystem example
  5. Three functions of digital twins
  6. A possible Internet for Things (I4T) ecosystem
  7. Iotic Labs “Lego”
  8. BAM Nuttall and Iotic’s learning camera application to monitor machines

 

[1]A suitable level of security and manageability is obviously required too. More on this later.

[2] Places on the Internet may be freely viewable to all comers or need permissions such as user IDs and passwords, for example.

[3] Kevin Ashton was a Procter & Gamble Executive who headed the MIT Center at the time:   https://www.forbes.com/global/2002/0318/092.html#7a164e0f3c3e. He is regarded as the author of the term “The Internet of Things”,  https://iot-analytics.com/internet-of-things-definition/

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Elisa Smart Factory: How to win over industry leaders in two years

Elisa’s Smart Factory solution

As STL Partners has described in The Coordination Age: A third age of telecoms, moves are afoot in the global digital economy to improve the efficiency of resource utilisation by combining the digital and physical worlds in new and innovative ways. Elisa’s Smart Factory solution is a prime example of how telcos can address this need.

Coordinating manufacturing

In the case of manufacturing industries, understanding and managing the flow and progress of materials and goods through production processes has long been a critical component of business success.

Managing and continually improving complex processes is central to operational success on the supply-side of the manufacturing industry. This includes everything from a floor manager overseeing production, to time-and-motion studies, total quality management, just-in-time production, robotics and automation, and many other managerial and operational approaches.

A number of new concepts and practices are now emerging, driven by the same imperatives but arising to a degree independently and in different disciplines, for example:

  • Industry 4.0 ‘the fourth industrial revolution’ – the trend of automation and data exchange in manufacturing industries
  • Digital twins – a virtualised version of a real thing, a bit like an avatar but for a thing rather than a person. It can simulate the real item, interact with it, and exchange information and commands with other digital twins based on pre-defined rules
  • The Industrial Internet of Things (IIoT) – connecting industrial devices, sensors, equipment, etc., to gather and exchange information, and sometimes perform remote control

Numerous companies have embarked on the journey to incorporate and use such connected technologies. However the degree of progress made varies greatly.

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A growing industry

Connecting machinery is far from a new idea. Many industrial machines and processes are already highly connected and automated, and this goes back as far as sixty years in SCADA (Supervisory Control and Data Acquisition) systems in electricity power station control.

What is new is the ability and desire to link these systems together and allow data exchange and a degree of autonomy within managed bounds. This can optimise performance, improve productivity, and ultimately lead to new operational business models.

There are many different possible paths to achieving these ends. For instance, powerful industrial players and consortia are all trying to establish leadership in different ways. Heavyweight contenders on the industry side include GE, Bosch, Siemens, and PTC, with consortia including the somewhat mystically titled All Seeing Alliance.

STL Partners will explore the wider opportunity and main players competing in this field in an upcoming report titled ‘Why we need an Internet for Things’.

Enter Elisa, the innovative Finlander

Elisa is the leading Finnish mobile and fixed operator and No.2 player in Estonia. It has 6.2 million customers.

Yet despite its relatively small footprint compared to some of the industry giants, STL Partners regards Elisa as one of the most innovative operators in the world, and certainly in Europe. Indeed, 18% of Finnish business customers say that it is the most innovative IT actor in its market, compared to 6% for CGI and 5% for Fujitsu.

One of its notable recent innovations is a totally automated Network Operations Centre (NOC). To create this, Elisa had to go through its own journey of process engineering and automation.

Elisa now resells its Elisa Automate NOC solutions to other operators. Similarly, it has leveraged the IP and learning to create Elisa Smart Factory, a solution to help global enterprise customers achieve the levels of success Elisa has achieved itself.

Our thanks to Henri Korpi, EVP New Business Development, and Kari Terho, General Manager, Smart Factory at Elisa, who talked to us openly about the proposition, the business, and how it came into existence.

Contents:

  • Executive Summary 
  • Introduction
  • Understanding manufacturing customers’ problems
  • Unplanned downtime
  • Unstable production quality
  • Lack of visibility
  • Practical obstacles to smart manufacturing
  • How Elisa approached the solution
  • Creating a service operation centre
  • Smart Factory’s claims
  • How did Elisa get here?
  • “There’s loads of discussion of which platform is best. What you actually need is a solution”
  • Conclusions
  • Success factors and lessons for others
  • Challenges
  • Next steps

Figures:

  1. Downtime, data usage and visibility – the three dogs of manufacturing
  2. Elisa Smart Factory Schematic
  3. Elisa Smart Factory screenshot
  4. Typical business objectives of Smart Factory solutions
  5. What an Elisa 3D Digital Twin looks like
  6. A high level view from Elisa’s “End-to-End Cockpit”
  7. Results from Elisa’s automated NOC

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