New World of Work will be center to Factory of the Future

Last week at a conference, a couple of my colleagues and I had the opportunity sit and debate the changing world order that will make the “factory of the future”. The three of us are involved in the major opportunities we see in the market and it provides us the real opportunity to engage with companies with transformation plans, and engage with thought leaders. We decided to approach the discussion of the future factory by approaching it from different industries, as well as markets.

Sure enough we ended up aligned on the core to the “factory of the future” will around what two companies labeled “New World of work”. I have mentioned this many times in this blog around “smart operational work”.

We were able group companies who looked at the future thru "new technologies" and how they could apply them, (I seem to visited a number of this type in the last month) vs those companies that we believe will be the leaders with the successful approach of “how they must operation, work” in the new world.

We defined the new world means the next 5 to 10 years with characteristics of:

•       Brand loyalty at customer reducing, so “Brand Promise” is key
•        Agility to satisfy is key
•        Shrinking mid tier market as the larger companies continue to consolidate to address the supply of new products and service markets. (especially in consumer products).
•        Dynamic workforce where workers rotate locations/ roles, experience in a role will be less than 2 years.
•        Supply chains with limited inventory requires transparent/ agile manufacturing across the sites.
•        “Constant Change” in assets, process, people, products is the natural state in the 2020.

The diagram below is an interesting on Agility:

The Sense of time shortening causing the decisions, lifetimes of products and lines and roles getting for ever shorter. The ability to rapidly introduce, change in not just product but also delivery, and supply is key in order to satisfy.

The fact that each of us engaging different industries such as oil and gas / process, to consumer manufacturing saw the core catalyst the leading companies have identified as the transformation in the way their company must react, capture and execute work. Shifting from isolated plants, and people to teams of plants and people that work as an aligned operational team to achieve a goal.

The “New world of Work” is fundamental built on :

• New ways of working with dynamic workers that share, collaborate and are connected but assume experience from the system, they trust the system
• New Processes around agility, new product  introduction that leverage the skills and approach of the “digital Native” collaborative worker, combined with new technologies to enable new processes and operational awareness. The ability to see situations early, continue to learn, and act fast to changing conditions is key.
• New technologies provide the opportunity to deliver these new ways of working, with new processes. The likes of leveraging the data, through “big data” to use the past to determine the future in a natural manner. The industrial internet of things (industry 4.0) will enable smart devices providing new levels of embedded autonomy in machines and processes, shifting workers to “exception based” management, but with greater responsibility.

The diagram below shows this shift, which will require different tools and approaches.

So as you look at your plans, are you stepping back and looking at the way you will work, then understanding the profile of operational team, how they will developing the processes to satisfy this work and required agility, and then looking at what technology you can leverage to accelerate the success in a sustainable and evolutionary way. This last comment is key as the natural state of the new world is one of “change” and the systems and culture must be able “master” naturally.

Can we achieve the last mile of operational Excellence without IOT?

This question was posed to me last week, and it is a good one. The critical items is to understand what is operational excellence is trying to achieve to realized that it is journey and moving goal of effectiveness pushed by the market and technology. Like when you are riding a wave, you staying in front, and leveraging the wave to excel, otherwise it swallows you up.

Operational excellence is about:

• Agility to deliver products/ services to Customer/ market at the correct price, time and location
• The ability to rapidly introduce new innovation value to lead the market and open new markets
• The ability to enable sustainable innovation and value through effectively leveraging people, and technology.

The diagram below illustrates this, and I am sure some people will have different angles, but it is about leading the competitive edge.

But can you achieve this with the traditional approaches? I believe you can get to 60/ 70 % of the way with traditional approaches and current technologies, but that last mile needs a paradigm shift in “actionable decisions”. Agility requires timely decisions across a team, and consistency and timely actions associated with the decision across teams, roles etc.

A core concept of Internet of Things (IoT) is teams of things (devices, and people) interacting in an orchestrated manner to achieve an operational timely result. With devices being more “self-aware”, empowered to take actions, interacting with workers or other devices to move “work “to the next step.

This foundation of IoT and the orchestration of devices /people, timely knowledge, provides that much needed paradigm shift to enable that last mile on the above operational excellence journey. The constant discovery of new capabilities, and knowledge through big data techniques, the ever increasing lake of embedded knowledge lends it as the basis for companies to go on this Operational excellence journey, but with this is the required cultural evolution to continuous improvement and knowledge/ wisdom.

                                       Source ARC

The above IOT maturity model matches to Operational Excellence journey, especially on the stages of “smart, and autonomous” linking to the Operational Excellence stages of “Driving Business and Driving the Market”). Foundational to Operational Excellence is timely knowledge and procedures being delivered so actionable decisions can be taken in a consistent manner across plants, assets and people. The IoT principles provides the opportunity to deliver this knowledge, while abstracting the variability in plant, assets and experience levels of people.

To me the desire and programs being enabled at companies to take them down the operational excellence journey provides the cultural evolution needed combined with IoT to succeed and make IoT effective not just from technology but most of all business side

Empowering a New Generation of Front Line Workers.

Recruiting and retaining talent is a top concern for management as the global workforce transitions to the “millennial” generation.  Every time I am in front company executives across industries and regions of the world, yes operational efficacy comes up, but always the deep conversation and search for ideas comes around the changing operational workforce, and associated workspace.

The diagram below illustrates the changing workforce:  

While mundane tasks will continue to get more automated, what work remains in terms of executing on the front-lines warrant a smarter workforce to deal with the corresponding rise in process complexity and product velocity of the value chain. Or a Operational System that abstracts this increased and evolving complexity into the system, allowing variability in the workforce experience and skill. In other words, for those on the industrial front-lines, the boundaries between physical vs. information work will continue to erode – which in turn, changes the very nature of the software applications to support these workers.  

The next generation of industrial software must be able to propel the productivity frontier to new limits while accommodating the new expectations of the Millennial workforce. Examples include:       

• Information at the fingertips: The information they demand to do their job must be equal to or better than their experience as consumers of mobile, social and collaborative technologies.

• Work to be rewarding: They can accept tough work conditions if it offers them the autonomy to contribute in their own way in order to keep them engaged and committed.

•  Change jobs more often: As opportunities to grow “up the career ladder” shrink, they will seek lateral mobility for growth, putting greater pressure on software applications to accelerate “time to proficiency” and performance consistency.

As I sit in the Karoo in Southern South Africa, on Easter weekend away with a number of senior managers of companies in different aspects of manufacturing. The conversations do discuss the future of economics, but the big discussion comes back to workforce transformation, skill set development and retention, and new culture and work method with the Gen Y, how to maintain their engagement and interest. In this country (South Africa) where there has been a significant departure of “baby boomer and gen x” over the last 20 years, leaving the current level of Gen Y in the workforce is already at levels of 2020 expectations in western world (40%).

The issue is how to train, retain, and develop skill and experience, so that companies maintain the required output efficiency. The nice part of the discussion is the reality that it is not a transition of workforce, that it is a totally new workforce that will engage, operate and work totally different to the traditional Gen X and before, and the development of an company/ operational culture that is exciting to attract and retain talent is key.

The big question is can this exciting, attractive culture/ experience be created in an economical and sustained way, especially in the current cost restrictive climate? This then leads to a discussion on the alternative discussion around “generalization “ of “activities” through templatisation of processes, and information, so that decisions and actions can be abstracted from the variability in the experience levels of the work force.  The key assumption is worker experience will vary, and your operational practices will evolve and improve with the business at an ever faster rate, the operational systems of 2020 need to enable a workforce of different skill sets to work in a consistent manner making consistent timely decisions and taking proven actions.

The airline industry has done this with pilots being able to move across different plans, meet their operational team ½ hour before flight, and key still act in a timely and consistent manner. Perfect example was the “Hudson River Incident” where the pilots met ½ hour before take-off, and in the 3 minute flight they took actions only speaking once due to repeatable proven procedures to achieve a successful outcome. 

Why cannot we do the same with the industrial landscape and systems, so that we assume that workforce will change, evolve and the operational systems can accommodate this change while maintaining operational efficiency??     

Multi-site standards have to be economically viable, but Operational Value of standards is the driver vs IT requirement

While flexibility allows us to deal with the plant floor reality, it also comes at a cost and thus requires governance. This is typically where the IT and Engineering perspectives tend to clash:

1. Standardization (what Corporate IT desires): How to deploy “out-of-the-box” or packaged solutions that reduce risk and time-to-value in implementation across the plant sites? Increasingly Operational value is driving standards and platforms.
2. Flexibility (what Engineering desires): How to support the various customizations to accommodate the heterogeneous nature of the process within a plant site?

But with the growing demand for agility and ability to absorb new production plans, new product introduction with minimal impact to day to day operations. Combine this the ability to “accommodate variability” in automation systems often from different vendors across multiple plants, or equipment, as well variety in team skills, and experience. The implementation of platforms combined with standards provide the necessary abstraction to “accommodate” this variation. So move to standards is growing driven more from the operational continuity drive than IT (which drove it based upon cost of implementation and sustainability).

To solve the above two seemingly opposable expectations, large enterprise users of a platform use a Center of Excellence approach to centrally manage the template library while helping orchestrate each of the plant’s technology roadmap in a way that is aligned to their Continuous Improvement journey.

The illustration below maps (at a high-level) the governance process of how templates are created, maintained, and modified to support the rollout across a multi-plant standardization effort.

Many of the most successful companies driving standards, are now seeing the rewards and return through agility to absorb new plants into their organization, yet leverage the existing unique automation, plant floor systems.

But so many of them comment to that they learnt the hard way the need for governance, yet site collaboration to make the standards effective and adoption successful. Too many state building standards from the corporate center out seems logical, but in reality so much knowledge is in the field and the need for capturing that experience back into standards is key. Plus the shift with standards away from a project DNA to more of “product” life-cycle DNA is key.

The important learning is that standards are part of a program, they part of learning, but return is significant now not just IT point of view but from an “Operational side” and this is where the significant economical returns are seen through operational consistency, and agility. Understand that standards is a program, clear understand the required governance to succeed long term, and investment up front with the field so the standards will be adopted. Combine this with clear kpis to understand the reason why your implementation a platform and standards so the value can be measured for the long term, as this is a long term initiative that must enable sustainable innovation.

The Workforce Crisis of 2030!! And how to start solving it now

“People, workforce planning will become more important than financial planning.” Rainer Strack

This is a statement from good TED talk by Rainer on his interpretation of the workforce challenge of 2030. Supporting much of what this blog has been looking at this past year, but bringing another angle. The key we both trying to get over it is not about the changing workforce it is about the operational workforce transformation to a new workforce landscape of skill shortage, labor shortage and cultural and people change.

You can go to Ted talk with the following link.

http://www.ted.com/talks/rainer_strack_the_surprising_workforce_crisis_of_2030_and_how_to_start_solving_it_now

A couple of extractions:

The investigation and determination of a significant workforce shortage by 2030, but starting now:

The required strategies that will dominate much the thinking

Rainer is talking general workforce, if you take this and bring it into manufacturing, industrial world, the shortages will be all more acute. As pointed out in other surveys from Accenture and others.

This shows in US survey results on filling skilled and highly skilled roles, below is worked example of mid sized company in mid west.  

This is why the move from knowledge to wisdom is key, and emedding of knowledge and wisdom , actionable decisions into the systems is key to accommodate the transformation to dramatically reduced dependency on skilled people. From Rainer’s and other investigations that Operational Systems of the future in the industrial market have 50% + reduction in dependency in skilled and highly skilled workforce.This Ted talk supports this will be the biggest issue in the next 10 years to sustain competitive agility. Like we have seen in 2014, I believe 2015 this acknowledgment and strategies building around workforce change will intensify.    

Applied Knowledge/ Wisdom Foundational to Internet of Things, and "Time to Performance" of Operational Teams

For the last couple of weeks, Stan DeVeries and I have been brainstorming around articulating this core area of the operational transformation, "the ability to have a system that can absorb workforce change/ turn over". Good example of this is with one company on the 2025 vision of "all knowledge/ experience in the system", this is capturing as much of the tribal "applied knowledge" that the experience operational staff are making decisions, and taking actions on and moving it to the system. If then applied in a "activity/task" based operational experience, a younger skilled user has the ability to select a "activity" and the associated knowledge/ information, and action are presented to him. Dramatically reducing the "Time to Performance" and increasing the consistency of operations, while increasing flexibility in operational workforce management.

The results of the discussions has brought the discussion around "Federated Wisdom, applied knowledge":

The explosion of information across industrial operations and enterprises creates a new challenge – how to find the “needles” of wisdom in the enormous “haystack” of information.

One of the analogies for the value and type of information is a chain from “data”, through “information” and “knowledge”, to “wisdom”.  In the industrial manufacturing and processing context, it may be helpful to use the following definitions:

·         "data” – raw data, which varies in quality, structure, naming, type and format

·         “information” – enhanced data, which has better quality and asset structure, and may have more useable naming, types and formats

·         “knowledge” – information with useful operational context, such as proximity to targets and limits, batch records, historical and forecasted trends, alarm states, estimated useful life, efficiency etc.

·         “wisdom/Applied Knowledge” – prescriptive advice and procedures to help achieve targets such as safety, health, environment, quality, schedule, throughput, efficiency, yields, profits etc.

The cost to store and share data has dropped significantly, and a simplistic expectation is that although storage is growing by a factor of millions in only a few years, that somehow the following pattern evolves:

Although the pattern might seem to be convenient, it is actually a nightmare, because it becomes much harder to discover and translate knowledge and wisdom from another operation, especially in another location, to the local needs.  But there is a solution.

To understand the problem better, let’s consider the definition of “knowledge” – it includes context.  This context begins with local context – time, location, process or machinery configuration, raw materials, energy and products being processed or produced.  It is already valuable to have “wisdom” to achieve and sustain best performance for the community, customers and the corporation.  This local context only needs to know its immediate information, if it has enough “wisdom”.

Now let’s consider what happens when a single site, a fleet of similar sites, or an enterprise have numerous similar operations.  How can local “wisdom” be enhanced by using “wisdom” from the other operations, especially when all of these operations are sufficiently different?

The reason that solving this problem is important is for operations transformation, such as operating physical assets as one (in a chain or as peers), and by supporting the multiple operations with a flexible team of remote experts.

One approach to solving this problem is to take advantage of a technique used in distributed databases, where a technique called “federated information” is used, especially in industrial operations management architectures.  This technique does not change the local information’s naming or structure, but provides multiple translations, both across the database for multiple similar structures, and for multiple contexts such as what financial, technical support, scheduling, quality and other functions require.  This technique is an alternative to the fragility and complexity of attempting to force a uniform and encompassing naming and structure that attempts to satisfy all applications and users.

The same approach can be applied for “wisdom”.  Currently, hobbyists and enthusiasts around the world share “wisdom”, for restoring cars, making furniture, playing a musical instrument, gardening etc.  Anyone with no experience at all can ask for “where do I get started?”, and most respondents will provide kind advice; in the same forum, experts can share wisdom that is valuable and understandable by them at their level of experience.  This “wisdom” is extremely decentralized, and the experts are providing the translation.

In the industrial operations environment, federating “wisdom” is partially automated by expanding the local context.  This expansion includes information about adjacent operations, information about the chain or peers if these operations are being managed as one, and then “knowledge” is expanded by applying the context of group targets and performance.

Some enterprises have hundreds or as much as tens of thousands of similar operations, supported by dozens or fewer experts.  Discovery of wisdom is greatly enhanced by maintaining an architecture which enhances local context without modifying or attempting to force burdensome structures on local operations.

Expect this discussion to continue as expand on the systems, and approaches to make this real, while enable sustainable operational innovation. This will be core to Industrial Internet of Things as we align smart devices, operational practices and humans into a dynamic but coordinated operational force.

Real time information Platform vs. traditional historian, Why it is Key to Pushing “Actionable Decisions”, foundational to the “Industrial Internet of Things” and Empowering the Teams.

Again last week I was presenting to a set industrial companies in water, food, and mining, and the topic of a "real time information platform" many questions.

My immediate answer is “what are you trying to do? " " who are the users targeted to interact with the system, and what decisions and actions are they expected to take?". These last two questions usually leave a complex blank expression on people's faces.

Many are engineers who have been asked to investigate, and they centered on the traditional approach of a "data centric" historian centered  world, leading with a technology strategy. The question of what people will use the data for, what roles and actions to be taken are secondary in their minds! 

Why is this when if someone had wanted a "historian" they would have asked for it. So why a platform, what does real time mean, and key is information.

It all comes back to one of the quadrants we talk about in the "operational transformation" around networking a series of assets, plants into a a "trusted" information system. That "actionable decisions" can be taken by a ever increasing community of operational people across the operational landscape.

To me it is understanding this community of consumers and what their requirements, uses are is key:

1. What activities, decisions, and actions they are expected to take?
2.  Their roles, skills, and approach is their time frame, location relative to the data
3. Their context and understanding of the plant, asset or process in question, as their is a growing trend of highly educated skilled people on assets, process. With little or no practical experience on the asset, and more than likely will not have visited site.

On investigations you find you have the traditional process engineers, who need the trend analysis and discovery of potential improvements. 

However, there is a growing tribe of people who need to make actionable operational decisions. They will not monitor the system must best "self-aware, and living" (exception based) capture the data, transformation  it into information.  Apply experience and knowledge, clear understanding of the situation, and what are typical actions with "best operational process" provided to take action.

This is very different to everything getting data stored and then extracted, yes in this new world there is history as it provides the history for reliable knowledge and basis for wisdom or " application knowledge".

The real key is the change in approach from “predictive to prescriptive” which embeds the “actionable decisions into the model. Empowering the operational team, no matter the location or experience with decisions and associated actions.

Understanding this maturity curve and evolution is what we see as foundational to the success of “industrial Internet of Things”. Through the embedded practices provides a basis for the changing workforce to act and make decisions in a timely manner.

However, these two communities in the industrial landscape are interlocked for success. The two communities are:

• Community 1: Process, performance, optimization team that accesses the data with trending, analysis, and predictive tools. Identifying the trends, conditions by applying their experience combined with “big data” techniques allows these conditions, to be seen in the “to be state”. If captured in a managed configuration framework, that will allow roll-out over sites and sustainable evolution. These become embedded into the system, for adoption by the operational team.

• Community 2: Operational Team: This is the dynamic team, from roaming people on the plant to central operational teams, to virtual expert teams, collaborating together in real time to enable “actionable decisions” no matter role, location, and experience.

The diagram below shows the this maturity of capturing this “applied knowledge” as Managed “Actionable Discussions” that interact with people, assets and process as key, very different a traditional historian approach.

The “Real Time Information Platform” provides a real-time "living" model that is self-aware that captures validates the data with rules aware of it is current state. Storing this data in context and rules and calculations in that provide motivation, embedded operational process, and awareness to correct people. Fundamental is the "trust" worthiness of the information, without impacting current automation systems. The ability to have sustainable evolution and scalability, through managed components that represent the assets and processes (actionable decisions) to the model is available on storage side in history and real-time.

You cannot do this with Historian (data centric) architecture and solution. Make sure you looked at who the communities of users you are satisfying now and in the immediate future?

The Perfect Storm in Industrial Operations = New Paradigm in Operational Landscape

I decided to revisit a blog that I have enhanced from over a year as preparation for a discussion I have been having with many people in the last 2 weeks around "realtime Information Platform" vs "Historian" which I enter that discussion in the next blog. Too many people are looking at one aspect.

The most significant disruption in industrial operational strategy is happening in this post GFC (global financial crisis) era.  This is focused on determining an operational execution environment which enables timely contributions by the operational team for sustained high-performance plant execution.  The focus is currently on operational processes, but this will shift quickly to driving a new operational experience which enables a new operational execution plan. Traditional user interfaces will not “cut it” both in products, or the way they have been implemented.

A common thread around the world is the operational personnel challenge, especially the finding of people to replace the existing “baby boomer generation” and lack of experience available in the market.

This is only part of the most significant disruption in operational strategy in the last 20 years, even since the introduction of the PC.  There is a perfect storm happening, with these vectors:

•        Ageing workforce: the significant number of highly experienced operations, maintenance, process workers who will retire in the next 5 to 10 years.  Some mangers in “oil and gas upstream” talk about the fact that 80% of their current team will be gone in 5 years.
•          Operational Agility means Decision NOW: to be competitive, decisions must be made now, this has caused a change in thinking that workers need to be empowered to make more decisions, through more information, higher knowledge and access to experience, and a transition from “worker” to “knowledge worker”.  This also means that they have much more responsibility.  As one customer recently stated, traditionally they had an operator cover 5 to 10 wells; this was fine when you have 100 wells which lasted 20 years, but in the next 5 years he stated “we will have 20,000 + wells, but we will not have 2,000 operators”.
•          The rotating operational person means “time to experience” is shorter than ever:the experienced generation is retiring and transitioning to an age group 20 years their junior, and there is a new factor that people are not staying in their role or location longer than a year.  One company stated 10 years ago that people were in a role approximately 5 years, but now they are seeing rotations of 8 months.
•         Transition to digital native worker, with very different expectations, causes challenges with worker retention: The new generation is “digitally native”; they expect access to knowledge, they expect “touch experience”, they expect collaboration from anywhere, and they expect to learn on the fly.

Stepping back and looking at all of these vectors; we have significant disruptions for those in charge of industrial / manufacturing operational execution strategies.

Addressing that significant disruption will require a combination of techniques:

•          A new generation of user interface products with more than interface capability, but embedded knowledge access, experience access, actionable procedures and natural intelligence, really empower the operational workers in all roles.
•          A new operational experience design.  Notice that the traditional enabler -HMI (Human Machine Interface) does not express this new design: as it is a true “operational experience” that goes through the “day in the life” of the new generation of operational knowledge workers.
•          New alignment across the different systems, plant applications and sites to align context, actions. Keeping the sites, applications and systems “loosely coupled but tightly aligned”.

Why?  Because today is not about Control Rooms; it is about agility and timely decisions, and this requires the “Flexible Operational Team” that works naturally together to leverage their experience, in the NOW to have decisions of all sorts made in a timely manner (often earlier than “now” to prevent instead of react).

The above diagram shows the concept of Flexible Operational Team, where at the bottom the traditional User Interfaces (UI’s) would have been permanently manned.  These UI’s are becoming transiently manned, but all functions relative to the zone of responsibility are available.  The more central operational centers (increasingly remote) will have a “quarterback” operational controller who is calling the shots, with a transient in-plant team of different skill sets, and a virtual team of experts usually external to the plant.  The in plant team executes activities that must be done locally, e.g. Inspections, maintenance, and certain manual operations, and the virtual team are experts across the world who can be tapped on for experience and knowledge to work with the controller or the in-plant team.

The above requirements is driving customers to look at the concept of “Enterprise Control”, providing the unification, and evolution of existing systems to achieve the alignment required to enable the concept of “agility thru Operational alignment and decisions in the NOW”.

The Invensys Enterprise Control Vision is to provide a set of capabilities that enables customers to achieve "Operational Excellence” through three strategies:

•          Empowerment of Operational People

Operational personnel (e.g. Operators, process engineers, process experts, maintenance, quality, production management) are empowered real-time decisions through operational awareness, access to experience, collaboration, and best practices in a proactive system, to perform multiple tasks, in flexible roles, in multiple locations.

•          Unification through Federation across assets, applications and systems

Align the different assets and processes across the operational management layer (of the traditional automation levels) so that the industrial operations are more agile (can change equipment configuration and use of the equipment much faster and much tighter coordination).  These assets that reside within a plant, within a process and across multiple sites are aligned to business and operational processes and require consistent measures and information.  Each of the existing applications/ controls continue to run, but their information and visualisation models are aligned, and communication happens with orchestration execution, in order for the Operational Process to execute in the most timely and effective manner.

•          Built on a Sustainable platform of capability so that the system has longevity to evolve.

Enterprise Control will be implemented in stages and evolve in scope, breadth and functionality through its lifetime at each customer installation, which could be 20 years.  The system has been engineered and architected in a way that enables this evolution to occur in a sustainable way and caters to changing engineering teams and technologies.

New technology products will enable the above operational/automation paradigms, satisfying the changes in the market and workforce, compelling all of us to think and engineer differently as we evolve our operational systems.

I am hoping this refresh and discussion answers many of the questions people have asked me lately, as it is not just about the ageing workforce, the transition, the whole workforce culture and approach to work will be different in 5 to 10 years, and it really is a transformation to "smart work" in the industrial operational space. 

The Paradox of the Growing Trend of Increasing Complexity in Industrial/Operational Solutions

I was discussing with a customer this week their systems, solutions, what was being asked of his team, and how even on a medium sized business and mature production processes the solution complexity is growing. He talked about the continued pressure of audits, regulations to satisfy government and just the consumer, combined with an increasing rate of " new product introduction" (npi). Yet production agility, timely actionable decisions, demands real time transparency into production, and across the supply chain.

Over two pots of tea we mapped out a high level functional landscape, his comment what happened to traditional  solutions. His comment was valid as the traditional supervisory solutions of 10 years ago, had transformed on the paper in front of us to "operational management architecture". With now an architectural landscape that connects to:

1.       Multiple vendor controllers and smart devices from ever increasing intelligent process equipment

2.       The range of people with different roles is increasing, in this example we have 8 different roles interacting with the solution, and taking actionable decisions

3.       The location of these people has shifted from the control room to every where, eg in the control room, roaming the plant floor, roaming the office, working remote outside the plant.

4.       Multiple applications that the system interacts with, has gone from to 7 This is not a big system, yes it is a batch system, but now cyber security, data transformation to deliver the correct trusted information for a role is available.

So complexity is increasing but the outlook is this will not change that business  will continue to demand more interactive, real times, collaborative, and transparent solutions in order to maintain competitiveness.

As seen below from an interview in North America, note the % of skilled and highly skilled roles, and the future additions of roles is in this skilled and highly skilled area:

So the complexity grows at a time when we have a transition to a less experience workforce, that will be in constant state of learning, and dynamic nature. In the conversation we talked about the team on his site, that he now had 50+ experienced and a junior engineer in his 20s. Fully capable but different, and less experienced on a site and role.

The diagram below shows the same people when trying to fill these skilled and highly skilled roles.

This is the paradox of today's dilemma facing engineers and operations, combine this with the demand projects with shorter project time, and that the system will evolve.

Now the control on the prices systems has not dramatically increased this is well defined and mature, it is the ability to absorb change that is key.

As we concluded our second pot of tea, it was clear the need to shift away from customer, home built solutions, away from customer excel sheets, to "off the shelf" solutions products that interact, can be easily configured and provide intuitive use, and learning, on an architecture that absorbs evolution and change. The discussion shifted to how transform their internal resources from internal customer code creation, to configuration, and acceleration of a more expansive solution building on their skill and knowledge.

The key walk away from this conversation, and why I shared it, was the realization by the customer that his approach to projects, and direction of addressing demands from operations needed a rethink in their approach, and using of existing staff, especially with the key experienced staff, and development of new staff. This included looking outside their own industry to potential significant advancements in addressing common operational approaches. 

Industrial Internet of Things: What does it mean to me?

I must have sat through 3 to four presentations of IoT in the last 2 weeks from different vendors, different industries. Combine this active strategic discussions within our development teams, you see many angles and thought approaches.

ARC’s definition:

“The industrial internet of things is a collection of technologies that can come together in a targeted  solution to improve business performance and machine availability”.

The key is the transition to information driven system has begun and it is about alignment of devices, process and people, to be effective in real-time agile production. Extending across the plant, and the whole value supply chain, providing transparency in end to end operations.

All are valid, but the question was asked on a site visit last week " what does it mean to us?". So I stood up and went to white board and drew three circles and intersected them, to represent the opportunity.

As you can see below in the diagram below:

The three circles were

1/ The Capital Assets, these a non-living devices, such as instruments, machines, motors, conveyors, tanks, PLCs, DCS, RTUs, switch gear, etc.

2/ The Human Assets: all the workers and roles no matter of location, if they employees, contractors, consultants, but are required for the efficient, timely operation of the production facility.

3/ The Operational, Product Processes, procedures that applied across multiple capital assets, across workers, and between chapati all assets and workers to gain consistent operations, production. Increased production consistency, increased utilization of all resources both capital and human assets, making the most effective use of resources such as materials and energy.

To many people refer to IoT are just looking at assets and smart devices, and moving to asset management, this is only a initial step, when you improve operational productivity out of the plant is when the paradigm of value is achieved. To me it is not just about smart devices, it is about combining this with proven production procedures, processes across the different assets in plant, both human and capital in order to gain must effective, efficient production.

Taking the customer a little by surprise, as they just been hearing about smart devices, but when brought relative to their plant reality sank in. Why is different to the traditional approach, is that when you think as in diagram below (from ARC) maturity of devices in the IoT as they become smarter to autonomous.

The devices, assets such as packaging machines, motors, pumps, agitators become fully aware of what is running in them, What they are meant to produce and how Their ability to achieve the desired result Their health and readiness to perform to expected capabilities. 

The machines move to been just apart of the team, enabling awareness to operational workers as early as possible of abnormal conditions that will effect production output, so " actionable decisions" can be taken. So when I walked around their plant I found the human assets all the different roles, and there were many, today they running between fixed work stations, looking uncomfortable in executing tasks, and doing paper inputs all over the place, totally in adhoc actions.

In the potential new world the human assets, are empowered with devices, from small, to tablets, to PCS, but they aware, connected, and the ability understand the situation. Combine this with the move to embed experience in the systems, so actionable steps can be taken in timely manner no matter where the worker is.

So the worker is :

• Now aware instantly of an up coming situation
• They can understand the context immediately
•  They can make a decision
•  They can take an action

All happening in real-time, no delays, and coordinated through exception based machines, processes, and embedded experience, so now assets, production and human workers are working as one.

Walking around this plant last week, the opportunity to take small steps in a coordinated operations and empower the workers to be effective, will yield significant returns. The internet of things in the industrial context is taking the operational / production co-ordination we have today to another level, extending the scope and understanding of workers, buy making capital assets and human assets apart of aligned team through embedded operational practices/ procedures. 

Knowledge must transfer to Industrial Systems to Combat the Skill Shortage/ Lack of Experts

A couple of weeks ago I talked about tacit knowledge and how it is key due changing way experts will be deployed, and short fall in skilled workforce. This was driven home again this week, with the release of skill assessment by “Accenture 2014 Manufacturing Skills and Training Study” that showed some real truths to the situation in the USA.

The diagram below show the current split of jobs that Highly skilled to skilled to unskilled, then the second shows that percentage of the Highly skilled and skilled jobs will grow over the next 2 years.

This is in total contradiction to the next set of questions around how severe is the skill shortage in customers.

The take away is that we putting in more complex processes, and systems in order to compete in the “flat world” which requires increased skilled people, yet there is reducing capacity in skilled, and highly skilled talent, actually the pool is shrinking.

The study goes on to talk about training and the use of operator training systems, and the need for intuitive (self learning) systems. But my thoughts rang back to discussion on Tacit Knowledge and how critical it is to capture experience not in words, or videos, but in systems that enable actionable decisions (built on embedded captured operational experience). Examples are Embedded operational Procedures, simulation for the future, pattern recognition on conditions to see events before they happen, all new techniques just entering the operational systems.  

Tacit knowledge is not easily shared. Although it is that which is used by all people, it is not necessarily able to be easily articulated. It consists of beliefs, ideals, values, schemata and mental models which are deeply ingrained in us and which we often take for granted. The key to acquiring tacit knowledge is experience. Without some form of shared experience, it is extremely difficult for people to share each other's thinking processes.

Tacit knowledge has been described as “know-how” – as opposed to “know-what” (facts), “know-why” (science), or “know-who” (networking). It involves learning and skill but not in a way that can be written down. On this account knowing-how or embodied knowledge is characteristic of the expert, who acts, makes judgments, and so forth without explicitly reflecting on the principles or rules involved. The expert works without having a theory of his or her work; he or she just performs skillfully without deliberation or focused attention. Apprentices, for example, work with their mentors and learn craftsmanship not through language but by observation, imitation, and practice.

The study goes on to provide examples of the impact of this shortage for a midsized $500m complaint to be $4.6m loss annually:

Food for thought!!! Tacit Knowledge must be captured in a form that new users can take actionable decisions in a reliable and effective way, through knowledge and experience moving from the experts to the systems in a sustainable approach that can evolve.

Clear KPIs for Measuring “Smart Plant/ Factory” Success is Key, Again Operations, Humans are Difference in this 4th Industrial Revolution

I seem to have been involved in Smart Fields, Smart Facilities, etc for years, and a lot of the discussion and thought leadership was around information, and more intelligent devices. But many have had limited success, until now, why is because many “smart” strategies did not cover all the bases.

During last week a colleague and I had a number of workshop sessions around forward strategy, reviewing specifically what is different this time round with smart, looking at the “Operational Transformation” event we seeing unfold, what is different and core this time! It was very clear, but so was the significant discontinuity in the market.

When we talk Smart concepts too often, the discussions goes quickly to the “smart/ intelligent” devices, and data and information, with the hype around the “Internet of Things” this continues. But when you really get down to what people are trying to achieve is decisions faster, and flexibility / agility through awareness and operational transparency.  

Yes the real impact here of this Operational Transformation is not just that devices are becoming smarter, “self aware” but the need to gain consistency in operations, and reduce errors. There is significant discontinuity happen in the market, as the logical way to eliminate the errors is through experienced workforce. As we all know that actually the workforce in 5 years will dramatically be less experienced than the workforce of yesterday or today.

The diagram below shows the experienced workforce  today is responsible for most of the unscheduled shutdowns.

So the outlook in the next 5 years is grim as we move to the in experienced workforce, unless our systems and operational processes change that is why “smart xxx” is real.

The major outcomes of the drive towards “smart factories, airports, fields etc” is to embed the operational experience, and self awareness in the Smart Devices” and “Smart Processes” .

Too often we do not have clear goals, but it was interesting to see a leading coming define very clear goals constantly to monitor the direction, and success of this "journey". 

Below is their goals:

Key drive is for zero human, equipment and process shutdowns and errors; this drives towards a significant embedding of process and automation on process and analysis to predict situations so that planned / controlled actions can take place limiting unnecessary shutdowns.

Key is the recognition that number of experts that are going to be available due to new generational work-space is going to be limited, and it is key to dramatically reduce the dependency on these experts by 90%. Another shift is to Global centers of excellence that must have access to timely information in context and trusted to interact with the local teams.

100% optimization of Feed/ Energy/ and Product usually plant have 1 maybe two of these tuned , but not 100% optimized, but this is not as simple as it looks when Feed stocks vary, Products instruction is increasing and Energy is totally variable, but the company has recognized to minimize impact of variability is optimization.   Also the knowledge of the system must be embedded, so the system is intuitive and self aware, enabling operational workers to rotate while maintaining consistency in operations and process.

Intelligent Alarms, and awareness will have to natural, so state / condition pattern analysis the move to the “to be” state is key. Many companies have significant programs in play now for transforming their current alarm structure to enable rapid, intuitive awareness of where that “pin” is in the haystack of alarms, and events.

As the plant becomes more intelligent and able to operate, key decisions and follow through actions in a timely manner are fundamental. This will not be one person; it will be a set of actions, and decisions across a team. So the operational system will be designed with collaboration in mind, the natural ability to guide, have built in operational process, natural documentation of actions, and passing of actions to the next person. Key will be the ability to “Resolve Operational Tasks” through tracking and an operational work system within the system, optimizing the human assets as much as the physical assets and processes.