In order for businesses to adapt to the concepts of the Industrial Internet, they need to realize the company’s current position regarding their processes, procedures, philosophy, strategy, and current technologies in relation to the level of adaptation they wish to achieve. Then there is the thorny issue of the actual means to achieve that objective. A common question arises, “how do we get from where we are now to where we want to be”?
For companies to adopt and take advantage of the enormous opportunities of the Industrial Internet and Industry 4.0, they will have to make some radical changes in every area of their business. The first and foremost prerequisite to adopting an IIoT or Industry 4.0 strategy is that of transforming the business to operate seamlessly in a digital world. There are many approaches to digital transformation of the businesses, but the common consensus is that it involves addressing three key areas—customer experience, operational process, and business models.
Digital Transformation
The concept of digital transformation—which is the use of technology to improve performance—is as hyped as the Industrial Internet and is a hot topic of interest in the C-suite, and for good reason. Executives are seeing industries in all sectors benefiting from digitalization by using the latest digital technologies such as analytics, mobility, social media, and smart embedded devices.
Digital transformation is industry agnostic and is certainly not confined to technology startups, which may admittedly received much of the media limelight. Successful digital transformation projects are present across an array of modern and traditional industries, from banking to media to manufacturing. However just as digital transformation can affect all industries, it can also involve all core functions of a business, such as their strategy, processes, and procedures.
CapGemini, in conjunction with MIT Center for Digital Business, came up with the term digital transformation. They proposed an effective digital transformation program should look closely at not just what needed digitized, but how it could be accomplished.
Some of the key points from the CapGemini proposal was that business and IT must be closely aligned and work together to obtain digital transformation. They saw that the Business/IT relationship was key and both had to focus on the same challenges and ultimate goals for the program to succeed. This is extremely important because some proponents of digital transformation see it as a business led initiative that will be achieved with or without IT’s blessing and participation.
However, that is a dangerous path to undertake, as IT in any business should always be aligned to the business strategy. Therefore, it is imperative that IT is fully engaged partners in the project or it will ultimately lead to disconnects and gaps in the program. Consequently, CapGemini recommended that the project be sponsored and championed from the top to ensure buy-in from all departments and stakeholders. Digital transformation is an extremely tricky project to manage, as it addresses core elements of the business, but neither customers, partners, or the competition are going to wait for change to happen. Change needs to be driven forward from the top.
CapGemini also suggested that opportunities in digital transformation existed in all industries. Furthermore, huge opportunities existed in efficiency, productivity, and employee enablement. However, to leverage those opportunities means transformation management intensity across all departments, stakeholders, and employees.
Furthermore, McKinsey suggests that digital transformation can reshape every aspect of the modern enterprise, with four core elements:
Connectivity with customers and partners
Innovation of products, business models, and processes
Automation by replacing labor with technology
Decision making by utilizing Big Data and advanced analytics
McKinsey proposed supporting these core activities and goals, with a cycle of functions of continuous improvement:
Customer experience—Entails seamless multi-channel experience, and whenever, wherever service capability
Product and service innovation—New digital products and services and co-creation of new products
Distribution, marketing, and sales—Targeted higher returns on investment through optimized digital marketing and sales channels
Digital fulfillment—Depends on automated processes and provisioning from start to finish
Risk optimization—Focuses on embedded automation controls with risk profiling as well as by improving customer in-sight
Enhanced corporate control—Improved real-time management systems and management dashboards, with seamless integration to the value and supply chains, including third parties
The big question is how a company shifts from where they are now to where they want to be through the digital transformation program. There are many roadmaps, which a company can follow on their journey toward digital transformation. However, not one roadmap fits all businesses or industries; each company’s motivations, intent, goals, priorities, budgets, and pain points differ.
Additionally, most companies are not ready for full digital transformation and they only want to digitize certain areas of the business, such as addressing the customer experience or sales and marketing processes as they can reap early returns without too much risk of disruption to the core business. Another long-standing problem, especially in the traditional industries such as manufacturing, is the concept of functional silos and the need to work across those areas of functional and political segregation. For digital transformation to work, there must be minimum, preferably none, silos existing within the business. Unfortunately that is rather difficult in traditional industries that have a hierarchy of departments. For example, in manufacturing, the production departments—those that make money and are the sole reason for the company’s existence—have seniority over the support departments such as IT or HR. Convincing these senior departments—such as manufacturing, engineering, logistics, finance, sales and marketing—to relinquish some of their status and influence is fraught with problems.
Ideally of course, all departments should cooperate for the greater good and learn from each other in order to boost productivity and profits. However, for that to work in practice, the CEO must understand the huge potential of digital transformation and how it will affect each area of the business as only he or she will be in a position to drive through the silos and create the ubiquitous business and technical connections required among people, processes, and systems.
Customer Experience
Customer experience, sometimes called user experience, although they are not always the same thing, is one of the basic building blocks of digital transformation and one that is typically addressed first. The reasons are simply because it can produce results quickly using existing equipment or by leveraging social media on cloud services.
Knowing the Customer
Social media has become a tremendous source of intelligence for businesses as it allows them to discover what leads to customer dissatisfaction. Additionally, companies are learning, some quicker than others, to embrace social media and engage with their customers/users directly . At the heart of these initiatives is the goal to know the customers better, to know their likes, preferences, and dislikes regarding the company’s products or industry sector in general. If you can determine what customers’ dislikes regarding the way the industry is run in general, there is a possibility to steal a march on the competitors. After all, just like all closed groups, companies in industrial sectors are often blind to their shortcomings. They think this is the way we have always done this, and so has everyone else, so they don’t see a reason to change. However, getting constructive criticism from customers may be advantageous. An advantage of this is with the airline industry, before the advent of low-cost airlines, the customer experience was dreadful, checking-in was slow and tedious, as was boarding and the costs were high. However once a few pioneering airlines decided to cut costs they had to be sure that they would get enough passengers so they listened to their frequent flyers’ pet gripes, and low and behold they revolutionized not just the pricing structures but check-in, boarding, and flight-booking procedures.
Customer Contact Points
One of the major digital contributions to the business is by the increase of customer contact points . Before mainstream digitization, back in the 2000s, companies could be contacted by telephone or e-mail. Today, companies have click to chat or call to communicate with a live support agent on their web sites, or they have online forms to open service tickets on their sites for customers’ convenience. Other technologies are gaining acceptance, such as video calls using WebRTC, which enables a customer to contact a support center via a browser using video chat. This is proving important when technical support agents need to actually see the product and can make fault diagnosis and fault resolution much quicker.
Similarly, the massive growth in mobile apps has led companies to produce their own apps, which further integrates the customer with the company and provides even more intelligence such as location. These apps also can be used to send pictures or videos of a product to the customer. Similarly a customer can send media to the support center in order to assist a technician with a diagnosis.
Transforming Operational Processes
Customer experience may be the first channel that a company turns to digitize because of its importance and relative ease of implementing the new technologies. However, when executives are asked about the most successful and productive areas to be digitized, they tend to mention process digitization. The digital transformation of operational processes can reap very early benefits, sometimes termed picking the low lying fruit, so it is an attractive initial area to focus on.
Process Digitization
The benefits of process digitization extend right through the value chain from early rapid development and prototyping of a product, to automated production lines and efficient stock control and dispatch. Automation of production line enables workers to be freed to do other less tedious repetitive jobs, such as supervising automated processes and using their production and product experience in a quality-control capacity.
Digitizing processes also saves money as products and stock are more efficiently created and replenished using automatic stock replenishment procedures in ERP. Digitization facilitates a variety of stock handling and inventory controls, such as build-to-stock, build-to-order, or engineer-to-order. By moving away from the build-to-stock model to a much more cost-effective and efficient build-to-order can have a huge effect on the asset cost of inventory and on raw materials and parts.
Worker Mobility
Mobility is one of the great enablers of efficiency and productivity in the last decade. With the ubiquitous smartphone, employees are now mobile and initiatives such as BYOD (bring your own device) and even BYOC (bring your own cloud) have allowed employees to be mobile and work from anywhere at any time. This has greatly improved productivity and innovation. Similarly, VoIP PBXs have allowed employees to work from anywhere as calls from the company phone system can be redirected to any phone seamlessly and transparently to the caller. Therefore, employees can take calls when travelling, at home, or in the car, just as if they were at their desks.
VoIP PBX systems also seamlessly integrate with the Internet so employees can participate in conference video calls and remote meetings and presentations. Additionally, they can collaborate within these calls by sharing their desktops and using them as shared whiteboards, or by running a presentation. The opportunities for remote presentations and teaching are vast, saving companies not just money on travel and wasted time, but boosting collaboration and innovation across disperse groups of experts.
Performance Management
Performance and operational efficiency gains are the results of digital transformation. Digital information collated and presented as performance and KPI indicators in a dashboard format enables executives and managers to see exactly what is happening within the business in real time. This would have been impossible for most organizations a decade ago where some still relied on departmental status reports produced on Excel spreadsheets or unconnected propriety software.
Advances in system integration techniques, such as APIs (application programmable Interfaces) and web services, and particularly the advent of SaaS (software as a service), has greatly enhanced the ability to retrieve report data from disparate systems. This allowed businesses to collate and present operational and management data either as a dashboard or as the input to other processes.
Big Data and advanced analytics take this concept even further, as previously the analytics was historically based, with some vague trend analysis. However, in a digitized environment, data analysis software collects and analyzes data in real time. This facilitates the production of plan-to-performance analysis, which allows management to have visualization of all assets, projects, business units, and employees that they manage to see if they are performing as expected against their business goals. Plan-to-performance analysis will highlight not just the overall performance status but also provide granular drill-down reports on sub-projects or procedures to aide understanding of why the status is as it is. Furthermore, with Big Data’s advanced analytic capability, data analysis can now be historical, predictive, and prescriptive.
Transforming Business Models
Many business executives have enough insight into their own business and that of their industrial sector that they operate successfully. It is actually common to have managers who have enough self-awareness that they understand that change is imperative if the business is to survive, let alone grow. However, with digital transformation and the Industrial Internet, companies can change and adapt to new innovative business models.
Digitally Modified Business
The problem is that modifying a business strategy can lead to dire consequences. Take as an example a solid business that has been delivered through traditional means. An example could be a butcher shop that has delivered meat and cut joints as requested every week. However, the butcher learns about digitization and e-commerce and, staggered by the success stories, he decides to stop selling locally and sets up an online shopping market instead.
Strangely, we did see these ludicrous success stories in the media back in the late 1900s as local butchers claimed to produce and sell vast amounts of local pies, pasties, lamb joints, and other foodstuff on the Internet, regardless of logistics and production restraints.
However, the point is that modifying a business model is not always a good idea, and in fact it can be a very bad suggestion. The butcher’s current business model appeared to be successful, traditional, and well accepted, so why then would he want to change it?
To understand this, let’s look at how problems can occur.
New Digital Business
In order to create a new business or develop a new idea, you need innovation and tremendous amount of imagination, perseverance, and dedication. In the case of the butcher starting an online business, he would need to ensure that his current customer base would follow him and be positive about the change in direction. After all, the butcher’s customers may trade with him because of his traditional methods, as perhaps they also are not digitized, or even have that future capability. It would be inevitable that the butcher would lose more customers than he would gain by a complete digital transformation. The butcher would be far better to run the traditional business in parallel with a new digital business initiative, at least until he could gain experience in the nuances of online marketing by spending time and energy building an identity, a new customer base, and product lines suitable for trading in an online world.
The problem of course is even more profound when you’re launching new products or services and especially when launching a new business or entering a new digital market. The problem is that it is not easy to predict how customers will react and a startup company will inevitably struggle to deliver the goals and the goods at the outset until they build an identity and reputation. Therefore, it is not always clever to change the business model or technology just for the sake of it. Let’s look at one real-world scenario as an example.
A technological company that was unicorn rated at $2.8 billion as a startup, failed to live up to expectations and after a few years in development, having never traded, crashed and went bankrupt. This turn of events came about simply because the company failed to deliver a consistent product. The company was involved in mobile payments and it had a great concept, reasonable hardware, and a large niche market to fill—in mobile phones accepting credit card payments. However, the company that once claimed it would be larger than Google and Alibaba went bankrupt simply because it had no stable product as it kept switching to the latest technology—it was never happy with the technology that it was using. The problem, however, was not upgrading the technology per se, it was that each time the company had to embark on another mass marketing and advertising campaign to push this new technology, losing more potential customers than they gained along the way.
However, saying that, it is always sensible to look at alternatives and other business options and that is what makes digital business so popular. By analyzing data and performance figures, a company can ascertain true potential figures and trends, and thereby derive reliable trend analysis.
Digital Globalization
The whole point of digitization is that industrial industry and Industry 4.0 can span global networks. The global effect, that sense of collaboration and team building across borders, makes the IoT viable. Consider for a moment how industry could be feasible if each division of industry did its own thing.
If we consider that industry depends on true analytics, procedures, and manufacturing processes, we can say that these goals will produce an ultimate product. However, it is not always that way. If we analyze the data, we can see that the process of data to information, and then to knowledge, is not sometimes clear.
This is why we must consider collating data across a vast global environment in order to aggregate and then use that data lake as a pool for analysis. The larger the data lake, the more likely our analysis is going to be.
In order to meet global data acceptance, we must accept that the global data pools are not only trustworthy but essential in order to derive information and knowledge.
Increase Operational Efficiency
Consultants often stress the point that the whole purpose of the Industrial Internet or Industry 4.0 is about increasing industrial operational efficiency. However, that is only partially true. Industrial and business projects are targeted at providing efficiency, automation, and profits across the entire supply chain.
However, they are correct to stress the importance of operational efficiency as it is paramount to all business and Industry 4.0 lends itself to increased productivity, efficiency, and customer engagement.
Merge OT with IT
The biggest problem with merging OT (operational technology) with IT (Information technology) is that they have completely different goals and aspirations. It is actually similar to merging operations and development into devops. In reality, OT is about manufacturing and OT workers and technicians have evolved via a different mindset. OT workers have come through the industrial workforce, where employees are labor-oriented and expect that the job they do is vital to the manufacturing of the product.
OT staff work hard in difficult conditions and they work to meet production targets and work closely with the factory workforce as part of a team.
IT, on the other hand, is much more suited to the enterprise and the business and they use their expertise to guide other departments, to use efficient and productive methods and technologies. IT tends to lead rather than collaborate and that can cause stress, but either way the integration of OT and IT is hugely important to the business. Therefore, it is vital to first plan the convergence of OT and IT with an initial pre-convergence stage. During this pre-convergence stage, it is important to use internationally acceptable standards and to identify the company strategy so that there is alignment planned.
Once IT and the business have agreed on a convergence strategy, the actual process of converging OT and IT can begin. Convergence will be considered to be complete upon certain stage goal and milestones being achieved. These typically point toward a converged infrastructure where every device has an IP address and fall under a centralized network-management system. Once all the devices in the network are under the joint management of OT and IT, there is scope for collaboration in development and maintenance.
The next step after convergence is alignment. We touched on this earlier. IT alignment with the business is best practices and IT must ensure that it align its strategy and tactics to the company’s business strategy. We can consider the company aligned at an engineering and technical level when devices and systems are remotely accessible via the Internet. Furthermore, it is ideal if engineering and IT collaborate to chart all the applications and informational sources, such as disparate databases. Furthermore, it is best practice for IT to integrate all the applications, systems, and data sources with a common enterprise-wide identity and access management system.
The final step is to build on the systems’ alignment by integrating them all under the one planned architecture. It is at this stage that the company realizes cost savings, operational efficiencies, and competitive advantage.
The main point is that when merging the departments of OT and IT, management must carefully plan each stage before taking action; this is something that OT would find more natural than the more opportunistic IT.
Increase Productivity via Automation
An essential part of automation in manufacturing is to remove where possible any human action or interaction from the production process. A prerequisite to achieving this goal is that process controllers to systems, machines, and appliances can assign processing tasks. This is termed M2M, machine-to-machine communication, and within the context of human-machine-interaction, it is a vital component of the smart factory as it forms the cyber-physical systems. The CPS communicate through the Internet and, via the Internet of Things and services, produce new plant models and improves overall equipment effectiveness (OEE).
However, it is not just in industrial processes where M2M are commonplace, as they are ubiquitous throughout many business processes and indeed in any process where networked smart devices have a role in the process chain.
The networking of these digital things will also provide a huge spinoff for telecom companies and Internet service providers who will have to provide the traffic transportation between devices. Indeed, telecom companies are predicting huge increases in the number of SIMS and data modems integrated into all sorts of remote devices, such as vending machines, connected cars, trucks for fleet management, smart meters, and even remote health monitoring equipment, by 2020.
Automation is the way forward and, as we have just seen, it relies heavily on effective M2M in the process chain. M2M should play a large part in the business convergence and digital transformation process, as it not only improves productivity through overall equipment effectiveness but also allows for new and innovative business models.
Develop New Business Models
Industrial companies create their business models based on competitive strategy, which involves business differentiation, cost leadership, and focus. In most industries, especially in manufacturing, this strategy still holds true. However, with the advent of digitization and connectivity came new ways of looking at traditionally sound strategies in creating and capturing value.
As management shifts their focus toward digitization and perhaps a further evolution toward Industry 4.0, they should become aware of the huge opportunities for innovation to regard to value creation and value capture. Cloud-based services and techniques have enhanced the potential of value creation and capture to such a level that existing business models will require a rethink.
At the heart of any company’s business model or strategy is value creation, as it is the sole reason that most businesses are in existence. Value creation is about increasing the value of a company’s offerings—products or services—that encourage customers to pay for them or utilize them in some way beneficial to the business. In manufacturing and the product-focused business, creating value historically meant producing better products with more features than the competition. This required that businesses identified enduring customer needs and that they fulfilled that through well-engineered solutions. Of course, other businesses would be striving to fulfill the same customer needs so competition would ensue based on features, quality, and price. The strategic goal was to create and sell products with the hope that once the product became obsolete the customer would buy a replacement.
However, the Industrial Internet has presented an opportunity to revolutionize the way that businesses can create and sell products. There is no longer any excuse for the one-and-done product lifecycle, as manufacturers can track customer behavior and offer over-the-air updates, new features, and functionality throughout the product’s lifecycle. Furthermore, products are no longer in isolation. With the advent of the Internet of Things, connectivity is king and products can interact with other products. Connectivity leads to new insights and products through analytics, which improves forecasting, process optimization, product lifecycle support, and a better customer experience.
Consequently, modern business models are focusing on the customer, by creating value of experience. The Internet of Things facilitates business to view the customer’s experience in new ways, from how they initially view the product, how they use it, and what it connects with and ultimately to learn what more the product could do or what services or features could revitalize the product. Additionally, making money from the product is no longer restricted to the initial sale, as now there is potential for other revenue streams such as value-added services, subscriptions, and apps.
Similar to value creation, the way that businesses capture value has changed with the advent of cloud services, which leads to the monetization of customer value. Traditionally, at most product-driven businesses, value capture has simply been about setting the right price to maximize profits on discrete product sales. Of course, that is a simplistic view, as most companies expend a great deal of energy and creativity presenting and marketing their products and searching for key differentiators from the competition.
However, businesses can now maximize margins and leverage their core competencies to bring a product to market. Furthermore, they can do this while controlling the key points in the value chain, such as commodity costs, brand strength, or patents. They can also add personalization and context to lock in customers, which leads to recurring revenue.
Adopt Smart Architectures and Technologies
Innovation is critical in developing new business models and opportunities. However for companies to be able to fully exploit the opportunities they will have to master three core competencies—sensor-driven computing, industrial analytics, and intelligent machine applications.
Sensor-Driven Computing
Sensor-driven computing is the basis of the Industrial Internet as sensors provide the connection between the analogue world of our environment such as temperature, voltage, humidity, and pressure and the digital world of computers. Sensors provide objects with perception into their state and their surroundings and they provide the data required by systems to gain insights into industrial processes. Sensors only supply raw data to gain actionable insights and analytics.
Industrial Analytics
Industrial analytics converts raw environmental data collected from perhaps thousands of sensors into human understandable insights and knowledge. Analytics, traditionally, due to the limits of technology, had a focus on historical data, such as monthly sales reports. However, with the advent of cloud computing and mass data storage, advanced analytics has become commercially available to everyone. Advanced analytics now provide industry with historical, diagnostic, predictive, and even proscriptive analytical data. These advanced analytical algorithms provide insights into not just what has happened, but why it happened, when it might happen again, and what you can do about it.
Intelligent Machine Applications
Analytics have profound importance in industrial scenarios, as they provide the actionable insights that facilitate intelligent process control and proactive decision-making. However, to leverage the proactive benefits of predictive analytics requires intelligent machines , ones that are not just mechanical but have built-in intelligence. These smart machines will have self-awareness, not in philosophical terms, but an awareness of their own and their process’ current state through self-diagnostics. Being able to predict events in regard to component failure provides the methods to move from break-fix to fix-before-failure, which has profound economical benefits to industry. However, the real benefit of having intelligent machines is that they can integrate and collaborate with one another across domains. This enables developers to use innovation when creating intelligent applications.
Reaping the optimal benefits of intelligent connected technology requires a strategic rethink, technical awareness, and innovation. However, all that creativity must be based on a robust technical architecture and infrastructure, which requires an IIoT platform. The Industrial Internet platform is still at a level of immaturity so there are still gaps in interoperability and information sharing. Currently, this is the overriding technical challenge to businesses wanting a roadmap to the Industrial Internet.
Transform the Workforce
Back in the 70s, there was major concern among business leaders that production line automation with robots would replace the work performed by humans and effectively render them redundant. The problem was and still is that employees are the heart and soul of a company, unless of course you are operating a lights-out manufacturing facility. At the time, CEOs claimed that reducing the labor-intensive workforce from tedious, dirty, boring, or dangerous work was beneficial to the employee to the business. These business leaders managed to convince themselves that an automation initiative was humane and economical. Furthermore, it was an efficient way to boost productivity and efficiency while reducing costs and boosting bonuses. Unsurprisingly, trade unions and those whose jobs and livelihoods were at risk strenuously objected to this strategy, pointing out it wasn’t just them that were at risk.
Although it might have been attractive for CEOs at the time to reduce the payload and the operational expense and offload low-skilled workers, while investing in skilled IT generalists who could perform a variety of task, the premise was flawed.
Paul Krugman, back in 1996, imagined a scenario where:
“Information technology would end up reducing, not increasing, the demand for highly educated workers, because a lot of what highly educated workers do could actually be replaced by sophisticated information processing —indeed, replaced more easily than a lot of manual labor.”
Paul Krugman’s words have proven to be profound as we are now seeing automation replacing not just casual labor but highly skilled workers where market forces have seen skilled jobs replaced by software. Careers in software development and programming were once, even in 2012, promoted by universities and colleges as the work of the future, when they are now in the front of the automation queue.
It is an immutable truth that the labor workforce will reduce but the business will also have to transform in order to meet the requirements of the digital connected age. Businesses will require business analysts, strategists, data scientists, and those skilled in developing algorithms that match company strategy. It is one thing to collect vast amounts of operational data, but if you cannot articulate the correct questions and make sense of the returned answers, it is worthless. Consequently, reducing the head count of low-paid manual workers will be operationally beneficial in the short term, but any short-term benefit will be overwhelmed by the costs of expert hires as the company transforms to the digital age.