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When undertaking an Industry 4.0 initiative almost all organisations clearly understand that the initial step is for the C-suite to create and promote the organisation’s digital strategy. What is less understood and typically falls by the wayside is an equally important prerequisite to any business transformative initiative - planning and designing the Target Operating Model.
SMB Paths to Digital Modernisation
When an Small Medium Business (SMB) manufacturer looks towards modernisation or transformational initiatives they typically have a couple of options; one, is to abdicate the authority and responsibility to one of the big vendor platforms. This ‘buy in’ approach is favoured by the traditional brown-field sites. In this case the vendor will provide the platform and enforce their version of industry ‘Best Practices’ upon the risk averse organisation. The vendor has responsibility for the delivery of the deployment so the business must bend to comply with their ‘standard’ processes and architecture. As turn-key solutions these platforms will almost certainly deliver some expected value but alas they also may result in misalignment with the business vision or strategy, organisational disruption and fierce internal kickback. We will not consider this vendor approach further in this article.
Another path forward is the ‘build it yourself’ approach favoured by young ambitious greenfield sites. Unfortunately it too is not without its issues. Indeed all too often we see the Operational Technology (OT) team grasps the digital strategy and starts rolling out ad-hoc digitisation projects on the plant floor in a seemingly arbitrary manner. In fairness OT are generally successful in connecting up all those analogue and digital machine tools to a common bus. But that is the easy part and unfortunately any value created is contained within the factory’s plant floor domain (silo). However, if the OT endeavours are successful some will be emboldened to progress to launching digitalisation projects to share information across organisational domains (silos). Digitalisation, the sharing of information across domains creates much more business value but it is far more challenging. This is the point where most transformation initiatives fail; either in their entirety or they are deemed to meet some arbitrary goals but also to have fallen well short of stakeholder expectations, so are terminated. This typically is due to a failure to manage stakeholder expectations due to the lack of an overarching deployment strategy, which explicitly states the goals and objectives for value creation and serves as a roadmap to focus attention, maintain discipline, and keep teams on-track during execution and delivery phases. This is where the Target Operating Model comes into play.
What is the Target Operating Model (TOM)
The Target Operational Model serves as a strategic framework that defines how an organisation will execute its digital strategy and transition to a desired future-state, The TOM is a high level representation of how the organisation can deliver and execute on the digital strategy. A Target Operating Model will vary in complexity depending on the organisation but for Small Medium Business (SMB) the simplest form will typically suffice. This simplified TOM format involves planning and designing the interactions between three elements; people, processes and technology.
To understand why we need a TOM we have to consider that the operating model acts as the bridge between strategy and execution. It is a method of applying the organisational vision or digital strategy to operational plans to deliver the company’s desired future state. This future state is where the organisation wants to be, it is the ultimate goal in terms relative to the businesses present-day position.
Unfortunately, if the target operating model is non-existant or simply not explicitly designed to focus on the organisation’s strategic priorities the execution and the overall initiative is likely to fail. Hence, the first step in planning and designing the target operating model is actually transposing the strategy to workable terms using Design Principles. Hence we can consider the organisation’s digital strategy as a set of objective criteria that the leadership, execution, and delivery teams can reference to evaluate the direction and coherence of the model with the as-built delivery.
There are two powerful reasons to use design principles when designing the Target Operating Model.
One is it really focuses everyone on what matters most - to create and drive value in the business. The second is that design principles align and then tether the business vision and digital strategy, which can be very subjective into a focused fact-based roadmap. Thus, design principles are utilised to articulate the organisation’s objectives, surface its strengths and weaknesses, then translate the digital strategy into the requirements that the operating model has to deliver. Another design principle, which is handy to keep in mind is in defining what are the distinctive capabilities and competencies that your organisation must support or retain, which will positively distinguish your company and differentiate your products and services from your competitors.
Where does the Target Operating Model fit into a Transformation initiative?
The Target Operating Model should be considered a prerequisite to an Industry 4.0 or Digital Transformation initiative, one of those things you should think about at the beginning because as the old adage goes, “Fail to plan, then you plan to fail”.
The primary reason that the Target Operating Model must come early in the planning and design process is that it will drive the interaction between the dimension of people, process, and technology. Too often today we see SMBs being driven by technology which is pushed on them by a platform vendor claiming universal best practices, and that is rarely an ideal situation. Consequently they will deploy new technologies but are still utilising the same constraints in people and processes and expect transformative changes. On the contrary, the Target Operating Model drives change through analysis of how to best deliver value to the business and customer. The Target Operating Model is the centre-piece which influences the further requirements for people, processes, and technology required by an underlying OT/IT architecture model.
A good starting point prior to embarking on any transformative project or initiative is to review the status quo with business value delivery in mind. This is simply because most existing operational models, which are termed Current Operational Models (COM) just need reorganising or tweaking rather than full blown design from the ground up. You might want to keep the following in mind.
What are the key principles that currently underpin the current operating model and are they working? If so, are they retainable or reusable? This links back to alignment with your business strategy.
How well aligned is the current operating model with the business strategy? Does it coordinate people, processes and infrastructure to deliver the value that resonates with your stakeholders and customers? This also links to your digital strategy and business model design.
Is the Current Operational Model potentially scalable and flexible enough to serve all addressable markets and customers?
Is the business constrained by the current model in terms of scaling, supporting new technology and processes, and/or rethinking new products, service, and market reach?
Does the current operating model support sustainable growth and/or impact? For example, if you’re looking to scale up delivery, does the current model enable you to do this in a cost-effective, financially sustainable way?
Does the current model support the technological resource demands of people , technology, and processes such as machine learning, real-time analytics and AI, which may be needed to enable you to access new or diversified income streams?
Does the current organisational structure allow sufficient capacity and diversity to develop critical strategic relationships?
Designing a TOM or Reorganising a COM
If your “as is” review unearths issues with your current operating model, which for SMBs it surely will, then you may decide to redesign your current operating model so that it is fit-for-purpose in the context of responding to strategic change or market disruption.
When rethinking your current operating model design, you may find it helpful to answer the following questions in the context of what is “to be” in the future state, and how this might inform changes to your target operating model:
Determining an Appropriate TOM and Sustainable SMB Architecture
The big question that many SMB manufacturers are weighing up is should we shift the organisation's Operation Model towards cloud deployment with its vast array of compute, storage, analytical services and virtual delivery models? Is it even now financially feasible, business desirable, or operationally practical to try to run on-premises these modern compute, data-heavy storage and analytical data engines with their vast upfront capital and operational overheads? Unfortunately these challenging processes and pursuits cannot be ignored if the business wishes to stay relevant. Perhaps a feasible alternative is to loosen the administrative and business control so that capabilities can be deployed in new areas that enable building competencies in innovation, product development, and global services in the third-party cloud.
An Operational Architecture for SMB Manufactures
The technological and financial challenges facing Industrial SMB organisations can be daunting, but advances in cloud computing—particularly in storage, analytics, security and edge computing—have come a long way, but don’t be fooled it is not necessarily cheaper, it's always a balance between Capex (Capital Expenses) and Opex (Operational Expenses). Some small SMB industrial sites are already adopting standards in site data collection, such as OPC Unified Architecture (OPC UA), a machine-to-machine communication protocol. Well established protocols and methods such as Publish and Subscribe (PubSub), which have been around since the early 2000s to alleviate bandwidth constraints on scale, are well understood and are commonly deployed on the plant floor. The challenges though are no longer about system integration of machine tools or even gathering and sharing the data locally as that is one thing that is well understood - especially today when local network infrastructure bandwidth is not a bottleneck and a constraint to scale - but storing and processing it is another matter completely. The vast quantities of plant floor data that even SMB manufactures are hoovering up and storing for all sorts of reasons is frankly unsustainable. Storing vast quantities of raw data in overflowing databases on-premise is not ideal but sadly all too common. Indeed, very often the collection and storage of raw data is for no constructive purpose as there is no local competency or technology scaled to analyse such vast troves of raw data.
Cloud Manufacturing (As-a-Service)
For the better half of a decade the large cloud vendors have been offering specialised Cloud Manufacturing as-a-service. These cloud-based services are designed to fill the often glaring gaps between in-house competencies and technology capabilities as well as to mitigate the vast costs and risk associated with running on-premise compute, storage and analytical solutions demanded by advanced data analytics, Machine Learning (ML) and Artificial Intelligence (AI).
Consequently, many SMBs are looking to take advantage of these developments and maximise value from Cloud Manufacturing services in order to optimise their R&D or their operations within the triple constraints of their People, Processes, and Technology. However, this solution is not a panacea for everyone. Indeed, some SMB manufacturers should consider a hybrid cloud architecture, keeping local technology and processing at the site and utilising the cloud-scale architectures for data storage and analytics. This hybrid architecture balances on-premises productivity with the advantages of cloud scale by introducing new technology, such as edge computing, to the existing site-level technology stack. Edge computing facilitates real-time site-level access yet enables access to the cloud in a secure, reliable way. With a hybrid approach it is helpful to consider the Target Operational Model at several operational levels:
A corresponding Target Operational Model will provide a suggested baseline set of components and processes that can be deployed to extract data from the site for processing in the cloud. This requires much forethought and planning as investment in the infrastructure to bring edge computing and cloud capabilities to industrial sites is not cheap. Moreover, you will also need to diligently define what data is actually useful and should be collected, stored and processed, locally or in the cloud or simply discarded.
People, Process, and Technology
Significantly for industrial leaders, many staff already have some knowledge that can ease the operational transition to a hybrid operational architecture. Some local OT or IT engineers are not going to be strangers to cloud-based processes or cloud technologies such as cloud-native applications, data pipelines, APIs, and real-time data streaming services. Those that have been trained in cloud technology or DevOps might even be able to develop such analytic-driven processes and algorithms themselves.
Although the technology and many capabilities are already available, few SMB appear to be deploying a Target Operating Model when bringing the cloud to their manufacturing sites. They may feel that planning is an ugly word in today's technology environments but developing a hybrid operational architecture does require careful choreography.
Indeed redesigning the operational model around a new factory architecture by combining Industry 4.0 disciplines, cloud-driven analytics, and cloud-native services, with a DevOps culture and proven processes can rapidly accelerate an SMB’s humble operational architecture and capabilities towards a future-state where they have the competency and capability to deliver cloud-enabled products and services, driven by Machine Learning, Artificial Intelligence, and Advanced Analytics on their own industrial IoT platform.
About the Author
Written by Alasdair Gilchrist, a technology polymath that has spent 35 years in the field of technology spanning roles as a computer technician, data analyst, network engineer, security professional, OT data engineers, cloud native developer as well as serving as an IT Director.
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