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ML Journal

ML Journal

Navigating Digital Transformation

It’s not enough to just automate. To succeed in today’s environment, manufacturers need to hyperautomate. 

Setting manufacturing right is hard. Manufacturers deal with a lot of complexity, variability, and uncertainty to design, procure, produce, ship, and sell the products that their customers already love or hopefully will like to use. Manufacturers struggle to do more with less due to increased customer pressure to deliver quality products faster and increased competition to get to the markets sooner.

Getting manufacturing right also takes time. Manufacturers are also constantly striving to improve their bottom line through efficient operations and cost management while also growing their top line through market share gains and new offerings and business models. The current COVID-19 pandemic has highlighted these struggles in a new light and showed us in stark contrast how the pioneers have fared well above the laggards. Success hinges on effective digital transformation.

Automation Is Not Optimization

Manufacturing is at the intersection of many disciplines, and manufacturers are not new to adopting technology to improve operational excellence and profitability. Incremental innovations get deployed everywhere throughout the production and business processes to cut down costs or cycle times, enhance product quality or performance, provide new product capabilities and better supply chain execution, and ultimately gain an edge over the competition.

These essential incremental innovations in products and processes are undertaken most often by the individual line of business (LOB) departments. Typically, each department operates independently or with a couple of other departments, trying to solve the problems at hand. Driven by ever-higher demand for increasing productivity and bound by time and limited resources, teams in most enterprises try to find solutions that solve their immediate needs and then move on. In other cases, most teams work with the silos of information they have access to, so the efforts and results are limited in scope. These incremental innovations provide gains, but even more significant improvements lurk in every corner of the supply chain operations.

Manufacturers are also increasingly deploying factory automation to improve quality, consistency, capacity utilization, and throughput. With automation, manufacturers can mass-produce quality goods faster and become competitive. A significant majority of manufacturers have also digitized their back-office operations by deploying ERP, SCM, PLM, and other enterprise software solutions.

“While building a fully connected enterprise is an advantage, it also brings about some disadvantages unless done right.”

 

Digitized enterprise operations along with automated factory operations have provided significant gains for manufacturers. Digitized and automated productivity solutions are most likely implemented on one or more process steps or value chain activities to alleviate a bottleneck situation, increase collaboration, or automate a routine procedure to make it more cost-effective, repeatable, and reliable. When one bottleneck gets addressed, others pop up. Excessive automation or optimization in one area of the value chain could cause issues in others and re-surface one or more of the three dreaded monsters of lean manufacturing: namely Muda (waste), Muri (overburden), and Mura (unevenness).

Automation and digitization are not new to manufacturers. They have been deploying these for the past two decades. On the one hand, production lines have benefited from automation and have grown much faster and complex. On the other hand, digitizing business processes and supply chains has enabled manufacturers to handle and build complex global supply chains. This operational complexity, supply, demand, geopolitical, economic, and lately pandemic-related uncertainties pose new challenges to manufacturers.

Industry 4.0 Enables System of Systems

By applying next-generation exponential technologies such as cloud computing, IoT, big data, AI/ML, and AR/VR, Industry 4.0 offers unprecedented digital transformation capabilities in leapfrogging operational excellence and creating new business opportunities. Industry 4.0, or manufacturing 4.0, is all about building cyber-physical systems. The promise of industry 4.0 is to break down silos, enable pervasive digitization, bridge the OT-IT gap, and build a scalable system of systems. IoT helps connect physical assets easier. Big data helps store and analyze large volumes of data generated by complex and high-speed operations. AI/ML helps with uncovering deeper insights from multi-dimensional and multi-variate data. Cloud computing offers a scalable computing infrastructure, and digital thread connects and brings all value chain activities together. Going beyond traditional automation, Industry 4.0 brings everything together.

The digitized and connected supply chain entities and activities allow manufacturers to build systems of systems where information flows end to end, and decisions can be taken quickly or sometimes automatically. The ability to digitally connect with products, processes, and most importantly, customers directly, makes new service-oriented and subscription-based business models possible. While building a fully connected enterprise is an advantage, it also brings about some disadvantages unless done right.

Manufacturers today manage complex supply chains and produce goods where many activities are sequential and interdependent on many other activities. Decision-makers must deal with a web of interlinked events and decisions, where their decision is based on something that happened upstream and will influence what happens downstream. Given that almost all manufacturing organizations are not entirely digitized, enterprise workflows often span multiple departments, myriad touchpoints comprising of manual, digitized, and automated activities. As a result, workflows have inherent inefficiencies and often span longer than expected timelines. Customer delivery timelines, product lifecycles, and business cycles are shrinking, forcing manufacturers to improve their efficiencies further.

Hyperautomation to the Rescue

Gartner coined the term hyperautomation in 2019 and listed it as one of the top strategic technology trends for 2021. In its simplistic terms, hyperautomation is a framework to automate the automation, allowing processes to complete faster and more efficiently, and be less error-prone. Hyperautomation is an approach that enables organizations to identify, vet, and automate existing processes that themselves could be automated. Tools such as process mining, robotic process automation (RPA), low-code application platforms (LCAP), and artificial intelligence (AI) are some of the technologies that enable hyperautomation. Gartner predicts that through 2024, the drive towards hyperautomation will lead organizations to adopt at least three out of the 20 process-agonistic types of software that enable hyperautomation. Tools such as RPA, LCAP, and AI are considered process-agnostic software, and can be used in any organization across multiple IT and business use cases.

“Hyperautomation is an approach that enables organizations to identify, vet, and automate existing processes that themselves could be automated.”

 

Hyperautomation builds on what Industry 4.0 enables and takes it to the next level. Industry 4.0 facilitates the creation of cyber-physical systems, where digitized entities connect to communicate freely and collectively to accomplish business objectives. The digitized and inter-connected machinery, factory automation, people, and business processes are critical for further automating some of the processes to increase efficiencies. For example, a hyperautomation script, upon receiving a predictive failure alert from a predictive maintenance model deployed, checks the automation cell machine’s inventory levels. If the part is not in inventory, the automation places a purchase requisition and schedules the maintenance with the part arrival date and machine failure timeline in consideration. As illustrated in this example, hyper-automation employs a systems approach to connect cross-functional activities, automates mundane tasks, and accelerates the processes allowing human experts to spend time on more important and higher-level tasks. Hyperautomation could also include automation tools, such as optical character recognition (OCR), natural language processing (NLP) for extracting text and understanding information in printed documents, or any AI/ML implementations to automate tasks.

Implementation of hyperautomation starts with the analysis of existing processes to identify tasks or processes that are bottlenecks or need automation to alleviate the pain of laborious and boring manual tasks. Various data, task, and process mining tools uncover operational characteristics and create a virtual map of the enterprise-wide processes. Process mining software analyzes all the data logs and transactional data stored in enterprise systems (ERP/SCM) to build a virtual map. Similar maps generated by other software tools or supplemented by experts help understand areas that need attention and the overall impact or value add through automation.

Once an automation scenario is identified, tools such as RPA, LCAP, and integration platform as a service (iPaaS) automate workflows and implement hyperautomation. AI augments and extends these tools to implement digitized processes and capture data in newer ways.

Hyperautomation offers many benefits beyond increased productivity, lower cost of operation, and speed to execution. It also allows manufacturers to implement multiple workflows to meet customers’ growing needs and come up with even more efficient workflows. Gartner expects that by 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes. Hyperautomation takes one step closer to fully lights-out and autonomous factories.

Back to the Future

Since year 2000, many Fortune 500 companies have gone bankrupt or ceased to exist due to increased competition from their digital native competitors. Today, the manufacturing industry is going through another inflection point because of Industry 4.0. At the same time, we are going through unprecedented times because of COVID. It is an understatement to say that the COVID pandemic has highlighted the importance of digitization. Yet again, in the face of dire challenges posed by the pandemic, digitized enterprises survived and fared well compared to the laggards. According to the Gartner Board of Directors Survey1, conducted in May and June 2020, 69% of directors say that the effects of the pandemic, economic, and social crises are accelerating digital business initiatives. Analysis of a recent McKinsey survey2 shows that 94% of respondents said that Industry 4.0 had helped them keep their operations running during the crisis, and 56% said these digital technologies had been critical to their crisis responses.


“Hyperautomation builds on what Industry 4.0 enables and takes it to the next level.”

 

Increasingly manufacturers are taking notice. The latest MLC survey research3 confirms that 54.8% of manufacturing companies believe COVID-19 has increased management’s focus on digital transformation. The MLC survey also highlights that those that have grasped the digital challenge, and an encouraging 26% say that they had now scaled their M4.0 efforts on a company-wide basis, more than double the result of two years ago when the figure was 12%. What’s more, a further 18% are now implementing M4.0 on a single project basis, again double the figure from 2019. Manufacturers across multiple sectors and sizes are at various stages of the digital transformation journey. It’s probably not too late for the laggards to embark on this journey. However, laggards need to make huge and concerted efforts to catch up and continue to be competitive.

Systematic Adoption

Digital transformation is a journey — it’s not easy, and it takes a long time to change. With this in view following approaches are suggested to embark on this journey successfully.

Corporate initiative — Digital transformation of an entire enterprise is a strategy that needs to be adopted and executed top-down. It’s an integrated execution as opposed to individual LOBs choosing what’s best for them. A dedicated steering committee or a governing body must oversee and ensure corporate-wide activities align with set strategic direction and goals.

Think system of systems — The end goal of an Industry 4.0 or Manufacturing 4.0 transformation is to create a digital enterprise that functions as one. It’s ultimately a fully integrated ecosystem of suppliers, people, machinery, partners, and customers. Enterprises and stakeholders need to view the implementation from system of systems point of view. Every entity in the ecosystem adds value; hence, interactions, integrations, and contributions need to be considered and measured.

Adopt a platform — Just as a strong house needs a solid foundation, the success of the digital transformation depends on the solutions used. Considering the complexity of the system of systems, adopting best-of-breed piecemeal solutions may not be ideal. Instead, consider a platform that supports Industry 4.0 capabilities, offers digital thread functionality, and provides standards-based open interfaces. It’s much easier when the foundation is built on a capable enterprise platform that offers maximum capability, extendability, and flexibility to realize the corporate vision.

Incremental approach — Digital transformation cannot be turned on at the flip of a switch. Furthermore, manufacturers cannot interrupt their production or other activities for longer periods of time. Organizations need to consider implementation pathways that are least disruptive and incrementally add value while delivering the desired results to run day to day business. Adopting a capable and scalable platform will make incremental adoption easier as you are able to start anywhere and expand gradually.

Skill-building — People are always an essential part of the digital transformation equation. While automation is seen as a job killer, it is in general, a productivity tool to improve working conditions and a competitive tool for the survival of the company. Enterprises must invest in employee education to be successful in this journey. Employees who understand the benefits of the technology and can use the technology once deployed become enthusiastic participants in the digital transformation journey.

“Gartner expects that by 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes.”

 

Given all the industry trends and the exciting productivity technologies and solutions available today, the laggards might still have a chance to embark on this digital transformation journey before it’s too late. The digital pioneers, at the same time, can build on their existing implementations to take their competencies to the next level. Manufacturers should not just settle for traditional automation. On the Industry 4.0 journey, enabled by exponential technologies, potential and possibilities are unlimited. Autonomous factories are not a distant future. Where are you playing?    M

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