Digital industrial transformation - General Electriccost savings, better products and new data-rich...

Technology Business Research, Inc.

January 2017

Sponsored by GE Digital

It takes a comprehensive platform to make the journey

Digital industrial transformation

2

DIGITAL INDUSTRIAL TRANSFORMATION: IT TAKES A COMPREHENSIVE PLATFORM TO MAKE THE JOURNEY

©2017 TECHNOLOGY BUSINESS RESEARCH, INC.

About the study

In partnership with GE Digital, TBR conducted a study in summer 2016 that analyzed the buying journey

and purchase behaviors of Industrial Internet of Things (IIoT) platform providers. TBR surveyed 170

decision makers at industrial firms in energy and power, oil and gas, and manufacturing, as well as

engaged in deep-dive interviews with constituents from platform providers, Internet of Things (IoT)

systems integrators, and customers. The results of the survey are encapsulated in this document.

Overview

TBR’s and GE Digital’s digital industrial transformation research investigates challenges facing industrial

companies implementing IIoT solutions: the complexity of the solutions, the diversity of available cloud

and software platforms and solutions, and the implications of industrial transformation on many actors

within the organization. This paper focuses on the journey to a solution, the wealth of factors to be

considered, and what digital industrial transformation platforms contribute to the solution, the industrial

transformation and the organization.

About GE Digital

GE Digital connects streams of machine data to powerful analytics and people, providing industrial

companies with valuable insights to manage assets and operations more efficiently. World-class talent and

software capabilities help drive digital industrial transformation for big gains in productivity, availability

and longevity. We do this by leveraging Predix, our cloud-based operating system, purpose built for the

unique needs of industry.

About TBR

Technology Business Research, Inc. is a leading independent technology market research and consulting

firm specializing in the business and financial analyses of hardware, software, professional services,

telecom and enterprise network vendors, and operators.

Serving a global clientele, TBR provides timely and actionable market research and business intelligence in

formats that are tailored to clients’ needs. Our analysts are available to further address client-specific

issues or information needs on an inquiry or proprietary consulting basis.

For more information

TBR has been empowering corporate decision makers since 1996. For more information, visit www.tbri.com.

This report is based on information made available to the public by the vendor and other public sources. No representation is made that this information is accurate or complete. Technology Business Research will not be held liable or responsible for any decisions that are made based on this information. The information contained in this report and all other TBR products is not and should not be construed to be investment advice. TBR does not make any recommendations or provide any advice regarding the value, purchase, sale or retention of securities. This report is copyright-protected and supplied for the sole use of the recipient. ©Contact Technology Business Research, Inc. for permission to reproduce.

http://www.tbri.com/

3



Part 1: Introduction — industrial transformation,

comprehensive platforms and the journey ahead

Digital industrial transformation is about getting ahead in business. The process involves extracting

additional value from industrial equipment by harnessing data from the physical plant to deliver

operational insights and promote teaming inside organizations, leading to process improvements,

cost savings, better products and new data-rich digital services. This follows the broader digital

industrial transformation trend in which companies are adopting disruptive technologies that

functionally change the way they operate and deliver services.

When it comes to developing and deploying a digital industrial transformation strategy, working

with an IIoT platform is the fastest, safest way to results. Platforms provide the essential digital

industrial components in a comprehensive, secure and flexible package. IIoT platforms enable

industrial transformation by providing the necessary

technologies, including analytics, machine learning and

artificial intelligence, instead of having to procure them

from multiple sources. Insights, based on data and

analyses created using these platforms, can then be made

available, with appropriate access control, to individuals

who need them throughout the organization.

But not all platforms are created equal. In TBR’s study,

most of the customers sought improved operations, increased production or improved service.

They were looking for enhanced capabilities and features, alignment to their business needs, and a

wealth of built-in features. Their greatest concerns were regulations, liabilities and security. Yet

despite being largely satisfied with their chosen platforms, many customers had to supplement

their primary platform with additional products and services. Each IIoT solution is unique, and most

customers needed to go beyond the platform to meet their unique needs. The journey to digital

industrial transformation is new for each customer, and most choose both an experienced

platform vendor and experienced systems integrator to ensure their success.

Study results show that creating and deploying a digital industrial solution is itself a journey in

which many parts of a company must participate, including operations technology (OT), business

management, IT, security and data science. For the project to be successful, companies must begin

with the end in mind and involve a range of parties in the definition, creation and deployment of

the solution. After deployment, the journey continues as the company is transformed, on an

ongoing, incremental basis, to be more agile and collaborative. Digital industrial solutions ensure

people in an organization get the information they need when they need it, freeing them to solve

problems and make decisions. The entire organization becomes more efficient and effective, as

well as more rewarding for employees, as people work together on business issues instead of

process.

“For the first time it was a complete

transformation that we were looking to

do. Our move was not just only to have

an IIoT solution, but we were looking to

modernize the entire IT infrastructure.”

— Project Manager, Oil & Gas, Canada

4



Part 2: Digital industrial transformation drives

growth, profit and customer satisfaction

Under digital industrial transformation, IIoT platforms create a system of assets to capture

operational data, create insights and pair them with insights from other critical company systems,

such as ERP, CRM and MES. This helps an organization compete in a rapidly changing business

climate by applying IIoT to gain insights into its operations to become more efficient while also

responding more quickly to newly identified opportunities and threats.

Digital industrial transformation changes more than the business; it changes the dynamics of an

organization. Employees spend less time on process and working in silos and dedicate more time

to collaborating and focusing on operational, product and customer service improvement. A digital

industrial solution improves both the business and its products and services, ultimately benefiting

the customer. A platform facilitates the data capture and the cooperation that brings forth

industrial transformation.

Among the improvements companies can expect are:

Operations and cooperation: IIoT systems provide everyone in a

company or its operations group with the information they need,

allowing employees to collectively focus on decision making, problem

solving and strategy.

Asset management: Company physical assets are tracked, monitored

and assessed to ensure optimal function and reduce downtime.

Efficiency: Reduced downtime and optimal allocation of resources

decrease costs and increase capacity.

Products and services: Monitoring and optimization improves product

and service quality and allows companies to serve their customers better.

Insights — unanticipated improvements: Digital industrial solutions deliver insights to help

companies identify both opportunities and problems. Insights include ways to improve

products and services, new market opportunities, or emerging negative trends that can be

countered.

Competitive position: Increased efficiency and improved products enhance the company’s

competitive position. At the same time, adoption of a digital industrial transformation

program reduces the threat that competitors are doing the same thing.

New revenue: For some companies, IIoT represents the opportunity to provide new products

or services, sometimes expanding or modifying the company’s business model. This includes

Take Action

Bring together people across the organization to agree on a first IIoT solution.

Choose a specific goal for the first solution, one that will generate measurable ROI.

5



delivering what were products as services, or leveraging IIoT-generated data to create

services. IIoT gives companies the opportunity to set up virtual marketplaces where they can

do additional business with their customers, and where their customers can meet to sell or

trade their services and IIoT data, models, and modules.

Companies can evolve and grow as a result of the new information, agility and collaboration

brought on by digital industrial solutions supported by IIoT platforms. Solutions are often extended

and modified as companies react to new information.

The need to evolve the solution easily and securely is one of several reasons why TBR recommends

companies implementing digital industrial solutions use an IIoT platform.

Part 3: Why use a platform?

Although an industrial transformation project may start with

a single application or use case and companies might

consider that implementation to be just another stand-alone

IT project, it is the first step toward a new way of operating,

which needs to have the flexibility to grow and change along

with the organization utilizing it. IIoT transformation is

different from most IT projects because each digital

industrial solution is unique to the company implementing

it, since industrial transformation is more deeply related to

core company processes and more parts of an organization are more profoundly impacted. For all

these reasons, the invention, design, implementation and deployment of a digital industrial

solution is best described as a journey — one involving more parts and more systems of an

organization than are typical of a targeted IT project.

Organizations with the resources and experience of integrating IT projects will consider building

their own digital industrial applications because the architecture is similar, apart from drawing data

from physical assets. However, the requirements for flexibility, extensibility, security, specialized

analytics and collaboration are such that the most efficient means to achieve results is the use of

an IIoT platform.

Energy & Power Oil & Gas Manufacturing

Most common driver:

Enhance, expand, and optimize product and service capabilities

Optimize operations and increase productivity

Optimize productivity and throughput

“We wanted to improve customer satisfaction and we wanted to more accurately respond to outages and restore services.”

— Director, Strategy and Architecture, Energy and Power, U.S.

“ We simply cannot afford to have any downtime. We also wanted to understand and predict maintenance needs.”

— Vice President and Controller, Oil and Gas, U.S.

“We wanted to have a system that could adjust quickly to the changing requirements of our clients and increase operational efficiency.”

— IT Manager, Manufacturing, Taiwan

“We needed to get precise and to the

minute operational level data regarding

our production process. Getting

operational level data also meant that

we could better schedule maintenance

activities and hence optimize the

maintenance costs that we incur.”

— Director, Marketing, Computer

Services

6



The bottom line is that platforms allow

companies to focus on industrial

transformation and not on technology, such

as the implementation of updates or changes

to their purpose-built applications.

TBR found that customers who chose

platforms were seeking the ability to tap into

enhanced capabilities, domain experience

and ease of integration in a way that aligned

to their business needs and provided a level

of built-in features and capabilities.

This is because digital industrial solutions are

not just single applications or projects and

they take different approaches than IT

projects. Because digital industrial solutions

provide a new, more agile way to operate,

supporting them with a platform makes

business sense because of platforms’

flexibility, extensibility and cost advantages

relative to single-purpose applications.

Platform selection criteria

Platforms deliver a degree of completeness unavailable elsewhere, ranging from connecting

machinery or sensors to storing, securing and analyzing the data those machines produce as well

as supporting the dashboarding of insights created on top of that data. Building on a platform that

provides flexibility and enables the expansion of capabilities to meet company needs supports a

digital industrial transformation journey that moves at a far faster, less expensive and more

business-friendly pace than grouping and managing several stand-alone systems. Compared with

building an IIoT system out of component parts, building on a qualified platform will usually cost

less, because a comprehensive platform includes so many necessary components and services. As

a company continues its digital industrial transformation journey and evolves its IIoT systems, the

comparative cost advantage increases.

Platforms deliver on a range of options for supporting digital industrial transformation, including:

Comprehensiveness: A platform provides all the necessary components of most digital industrial

solutions. These include security, device management, data and data flow management, data

storage, analytics, access control, and tools for creating user applications.

Flexibility: A platform enables the continual evolution of digital industrial systems by bringing

Efficiencies gained in development

7



together a pre-integrated set of components that allow rapid

creation and expansion of solutions, without the costs and risks of

integrating separate modules.

Security: With security built into the platform, problems are reduced.

Security is “built in,” so developers don’t have to build it into every

component. Platform security is maintained as changes are made to

components on the platform.

Data governance: Data generated by the digital industrial solution

must comply with government and company policies on location,

access, record-keeping and auditing. These policies are set at the

platform level, allowing data transformation, analysis and

presentation to take place without requiring specific governance

processes at each point in the process.

Industrial analytics: Platforms come with analytics capabilities that meet the requirements of

companies that must react rapidly to incoming data and thoroughly explore and exploit

accumulated data for insights.

Asset centricity: Data sources in a digital industrial system are not isolated from each other; they

are real assets in the real world. It is essential the system can report on and initiate actions on the

asset level, not just the sensor level. The assets can be further grouped, expanding the model to

include assembly lines and factories, or vehicles and fleets of vehicles. This not only expands the

power of the IIoT system but also helps generate strategic insight.

Extensibility and integration: Typically, customers extend platforms with their own systems and

systems from other vendors. To be effective, IIoT solutions must be integrated with other

important business systems. In evaluating platforms, consider how they can be extended, and what

other systems have they been integrated with.

Take Action

Identify the key requirements of your solution for security, device management, data storage and management, analysis, and user experience.

Evaluate candidate platforms against those requirements.

8



Ecosystem: Existing integrations with other vendors’ software and services make new integrations

easier. Similarly, a network of vendors experienced with the platform, especially service vendors,

make implementation and integration easier. Together, software and service partners constitute an

ecosystem, and the presence of a broad ecosystem is a positive sign.

IIoT platforms have modules and services for IIoT solutions. These include the ability to model

industrial assets and, increasingly, model frameworks for specific types of industrial assets.

Similarly, IIoT platforms have analytics and analytic model frameworks for industrial solutions.

Many industrial applications require both edge and centralized analytics, and the availability of

industrial analytics in both tiers of the architecture is another characteristic of IIoT platforms. Many

industrial applications have exceptionally high security requirements, and robust security is

another characteristic of IIoT.

The platform selection journey

It is critical an organization see the process as a journey from start to finish for the digital industrial

transformation to succeed. TBR found that, overall, customers choosing platforms have been

satisfied. But capabilities, as measured by satisfaction with features, function and value (total cost

of ownership), are areas of improvement. The choice of a platform should not be determined only

by the specific solution being built. Platform selection should be influenced by the company’s

future plans, such as investment or product road maps, as well as its preferences for internal

change management, partners and vendors.

Most customers surveyed by TBR reported

evaluating a number of platforms against their

own specific criteria. Among the top

considerations for the evaluation are:

Architecture — edge, cloud or hybrid:

Digital industrial solutions vary in

architecture, depending on where the

assets are located, and how quickly the

IIoT system must react. Some solutions

send data from different locations to a

central one for processing and analysis.

Other solutions involve data analysis at

the “edge,” close to the devices. Other

hybrid solutions involve both edge and

central processing.

Device and connection management:

There are a number of ways to connect

devices to either edge or central locations.

9



The choice will depend on where the devices are, whether they are mobile, the requirements

for bandwidth and latency, and cost. Irrespective of the method of connection, the devices

must be managed and secured. Requirements are based on the number of devices, their

locations and vulnerabilities, as well as how many will be added or removed and how.

Data storage and management: Companies will capture and integrate large and diverse data

sets. IIoT devices often generate various types of data at a very rapid rate, challenging

solutions to handle the volume, the rate of data uptake, and storing the different data types.

Once acquired and stored, the system must secure and manage the data. To identify storage

needs, anticipate which types of data will be acquired and how that data will be integrated.

Analytics: Analytics are the heart of the system, given they turn raw data into operations and

business insights. Analytics are used in both edge and central systems. There are two types of

analytics, and most IIoT systems use both. Operational analytics react rapidly to current data;

historical analytics are used to find new insights into physical systems. The users of the data

must be involved in setting the requirements.

Application development: It is important to assess the extent to which the platform supports

developers with tools for data management, analysis, mobile apps and dashboarding. The

platform should support a continuous delivery model, in which operations continue as the

application evolves.

Development environment: It is better if the same development tools are used for both

central and edge processing. The tools should provide flexible building blocks to

accelerate development while allowing modification, contributing to the platform’s

suitability for agile development techniques.

Users and user interfaces: It is important to consider who will be accessing the data and

analyses, and through what devices and interfaces.

APIs and integrations: Integration plans extend beyond data integrations to application

integrations. New systems will interact with existing ones.

Security: Security is based on multiple factors, including securing devices and sensors,

messages, data and network/connectivity.

Reaction time is another consideration. Some digital industrial solutions are built to react quickly,

and sometimes automatically, to new information. Others are using the data for deferred analysis.

Near-term and long-term requirements will be considered when choosing platforms.

TBR notes it is important not to treat these considerations as a checklist. Available platforms vary

greatly in each of these capabilities, as shown by our survey. Most IIoT projects require most or all

of the aforementioned capabilities. But the requirements for each vary greatly by company and

approach.

10



Choose carefully

TBR research found that most platforms claim strengths in all categories, but they vary greatly in

their ability to deliver against those claims. Because IIoT platforms vary greatly in capabilities and

projects vary in their requirements, platform selection is complicated and customers must choose

carefully to gain needed capabilities while optimizing for reduced complexity and costs. Even so,

the journey often includes the purchase of additional capabilities outside the platform.

Complexity: TBR found that most customers acquire additional capabilities to supplement their

platforms of choice. Our research found that, at most, 65% of customers said they got everything

they need from their platform in the category of device and connection management, a basic tenet

of IIoT platforms. However, there were certain areas of focus, including analytics and security,

where customers determined they needed more.

Analytics is one area where TBR found great diversity between advertised capabilities and actual

delivery, as reported by customers. Only 39% of customers got everything they said they needed,

while 25% developed their own applications and another 17% purchased additional third-party

applications.

Indeed, TBR views this critical aspect of IIoT platforms as fragmented at best: Some platforms

provide only reporting capabilities with some data visualization, calling it analytics. Others have

machine learning and cognitive engines, but without base models on which to build custom

solution-specific analyses. Many platforms provide only cloud-based analytics, which makes it

difficult to respond to new data, while others provide both cloud-based and edge-based analytics.

Another area where platforms vary is in security. Many platforms provide a level of security. But

almost 40% of customers sought out additional packaged or custom-developed security tools to

augment their needs.

Costs: No platform can reasonably be expected to cover every gap for every customer. But, given

11



that most have gaps to fill, a platform choice can also lead to additional costs, an important

consideration for customers evaluating a digital industrial transformation solution.

TBR research found that, when we followed the total dollars spent on platforms, the average cost

for additional software or cloud services, reported by customers we surveyed, was almost twice

that for the base platform license or subscription. These costs are separate from expected other

costs, including systems implementation, infrastructure, management and deployment.

GE Predix

Predix is GE Digital’s IIoT platform built specifically for industrial

applications. The platform supports a broad range of IIoT use

cases, including asset and exception management for

predictive maintenance, resource optimization and revenue

optimization, in addition to product and service enhancement.

GE Digital has deep roots in industry, but is a relative

newcomer to IT, so it has built up an extensive partner network

among IT vendors, including infrastructure providers, IT

services companies including systems integrators, and cloud

platform providers.

Architecture: Predix supports edge-based, cloud-based and hybrid implementations: Based on the

understanding that digital industrial solutions vary in the ways in which they’re deployed, and

speed is of the essence in industrial settings, Predix provides device management, storage and

analytic schemes that fit on edge, cloud or both in a hybrid setting. This distribution of processing

is necessary for some solutions, to provide necessary responsiveness. At the same time, this

capability makes the platform more flexible for future enhancements or refinements.

“Against IBM Watson, Thingworx

and others, I feel Predix has

excelled in security by providing

best-in-class, flexible and

configurable access and

authorization controls, hardened

cloud infrastructure and equal

protection across multiple

communication protocols.”

— IoT Solutions Architect,

Genpact, U.S.

12



Device and connection management: Reflecting its industrial underpinning and relative maturity,

Predix is unusual among IIoT platforms because it builds in an asset-centric view of devices. Most

platforms, especially cloud-based platforms, treat devices and sensors alike. Each sensor is, to the

platform, a separate device. That does not reflect reality, where a device such as a wind turbine or

pump will have many sensors. For analysis, reporting and initiating action, it is important the

system is aware that multiple data sources are embodied in one device. Predix provides the ability

to model individual physical assets and asset classes.

Data storage and management: Predix provides tools for data ingestion, storage, management,

and integration, tools that were considerably strengthened by the acquisition of Bit Stew, a mature

vendor of data management and integration capabilities.

Analytics: Predix draws on GE Digital’s industrial experience for analytics. The predix.io site, for

example, provides a wide range of prepackaged analytics engines for industrial applications, as well

as a set of Predix data dashboards for data analysis, with the idea of providing data-scientist-level

insights. Predix supports operational and historical analytics and creates a feedback loop whereby

historical analyses are used to refine both the operational analytics and the system’s response to

operational insights. Predix also supports descriptive, predictive and prescriptive analytics, allowing

the system to report, anticipate and drive decision making.

Application development: Predix provides a range of APIs and prepackaged microservices that

assist developers in managing and routing data, performing analytics, reacting to incoming data,

and creating dashboards that output Predix-derived data and insights. Microservices are software

modules that are used as building blocks in creating applications, allowing rapid development. At

the same time, developers can use their preferred language and tools. Predix supports modern

agile development tools and approaches that enable continuous integration and continuous

deployment.

Security: Predix embodies a comprehensive security strategy that combines governance and

certification, platform hardening, tools for creating and testing secure workflows, and continuous

monitoring.

Digital twin: Predix provides the ability to model industrial assets as “digital twins,” digital

representations of physical assets that embed historical and management data. This allows the IIoT

solution to manage and service the entire asset, not just the sensor. GE Digital is building digital

twins for common customer assets.

Community: Predix has fostered the creation of a developer community, using resources like

reference material, training modules, podcasts, videos and blogs. As a result, Predix developers

“I would select GE Predix [as best in class for device connection and management], as GE Digital has

deep expertise in this particular domain and its competency is much higher than other vendors”

— Business Leader, Enterprise Mobility and IoT/M2M, U.K.

http://www.predix.io

13



help answer each others’ questions and post code samples. As with all robust development

communities, this mutual support structure accelerates the development process and advances

everyone’s skills. Predix also provides a means by which components of IIoT solutions can be

shared or sold among users, like an app store. This provides a mechanism to extend and refine

Predix’s capabilities.

Industrial Experience: In TBR’s research, GE Digital was most highly rated for its security and device

connection and management capabilities. These built-in capabilities, cited as must-have

requirements for a platform, position Predix as a strong and potentially cost-effective choice when

considering the overall costs of ownership associated with a platform. This is thanks, in part, to GE

Digital’s historical focus on industry and the availability of pretuned analytics, specific to a broad

range of industrial equipment, as well as the predictive capabilities of GE Digital’s Digital Twin for

asset management.

TBR believes IoT and IIoT platforms are now rapidly evolving, moving toward increasing the

number of specific capabilities or components that more directly address customer needs. GE

Digital has addressed these wants with its own and third-party apps and services by positioning its

Predix.io site as a community forum and an industrial app and service marketplace. Leveraging the

user and developer community is the way platforms of all types expand, and GE Digital is

accelerating this growth by providing a market — a technique that has proved very effective.

14



Part 4: The journey

Creating and deploying a digital industrial solution is a journey. It involves

groups of people moving in a common direction into a new environment.

Once the solution is deployed, the groups will continue working together,

often extending the solution or creating additional ones.

When it comes to implementing digital industrial transformation strategies,

a stepwise approach is advisable. Companies implementing digital

industrial solutions will succeed by creating a strategic vision for digital

industrial transformation, while taking tactical steps with demonstrated ROI

potential, to establish the foundation for industrial transformations.

The road map: Defining the project and integrating participating groups

As every solution aims to more efficiently meet the needs of end customers, parts of the

organization that are not usually involved in either operations or IT will often be engaged. The

groups involved always include business management, IT and operations, specifically OT. Other

groups are often involved as well, including marketing and marketing intelligence, sales, and

planning and strategy. For every group involved, it is essential to enroll them, and to do so, it is

critical to incorporate their goals and ambitions for the company, as well as their concerns.

As the project is defined, some goals and ambitions will be deferred, so a road map is needed that

extends beyond the immediate project to future extensions or additional projects. This plan,

including future views, is the road map.

For the same reasons that a

platform is the best tool for an

industrial digital solution, it is

usually a good idea to engage an

outside firm to help design and

implement the project and

capitalize on experience in this

rapidly evolving field. Digital

industrial applications are different

from other IT projects, not only

because they involve other parts of

companies but also because they

are transformative. Customers, surveyed by TBR in conjunction with GE Digital, found that their

initial results included a strong positive impact on their businesses. Positive changes included

business value impact, such as positive revenue growth or cost savings. Negatives included time to

completion, disruption, work to implement and spend outside the platform.

Take Action

Build for the first solution, but keep in mind potential next steps.

Keep affected parts of the organization involved throughout the journey.

15



Following implementation, testing and deployment, it is important to bring together

representatives of affected business groups to evaluate the project, recommend process

improvements and identify next steps. The road map is an invaluable guide, but it requires critique

and improvement.

Part 5: Conclusion: Digital industrial

transformation is enabled, requires a

comprehensive platform

The journey of designing and implementing a digital industrial solution

institutionalizes a new, more cooperative, more agile way of doing business

that relieves employees from necessary but routine tasks. This frees them

to move the business forward and to react to a rapidly changing business

environment. Once a solution is in place, the industrial transformation

continues, shaping the company into a more integrated and agile business.

Platforms both facilitate the creation of digital industrial solutions and

make those solutions more robust, secure and flexible, while addressing

the rapidly changing business environment. A platform helps makes that

adaptation faster, easier and safer by providing the underlying data and insights that expand the

scope of their systems of record, incorporating physical assets and processes. This provides

everyone in the organization with a single version of truth while, at the same time, allowing

everyone to obtain the information they need to do their job. Employees spend less time obtaining

and providing data and more time leveraging increasingly valuable corporate data.

Comprehensiveness is a very important quality for an IIoT platform, often the most important one.

To minimize effort, cost, project length and risk, the platform should provide as many as possible of

the required services or components. Most of the respondents in our study needed to integrate

additional components. Choosing a platform with the broadest array of services reduces the need

for additional integration.

On average between 20% and 40% of customers surveyed by TBR purchased additional capabilities

outside their chosen platforms, showing that, in many cases, there is a need to fill in the gaps with

products from other vendors. In evaluating platforms, it is important to develop a clear road map

and shop carefully for platforms, looking for the platform that delivers against the greatest number

of requirements. TBR expects platforms to expand and improve, but the breadth of potential digital

industrial solutions is so great that customers will continue to need to look for comprehensive

platforms.

The bottom line, of course, is that digital industrial transformation helps the businesses perform

better. With end results such as increased inefficiency, product and service quality, and

organizational capacity, the destination is definitely worth the journey.

Take Action

Begin the journey of digital industrial transformation by identifying an opportunity to leverage IIoT to improve efficiency, productivity or drive revenue.

Choose a comprehensive IIoT platform that fits your requirements.

Digital industrial transformation - General Electriccost savings, better products and new data-rich...

Documents

Transcript of Digital industrial transformation - General Electriccost savings, better products and new data-rich...