Trustworthy Operations Management Solutions

I asked Stan to contribute a blog on a topic that he and I are asked, that of "trust worth systems/ data" this is an incredible critical item as we move to "actionable decisions"

Blog by Stan DeVries.

When younger workers are asked about how “trustworthy” solutions should perform, a common response is “it just works”.  This is a reasonable but demanding expectation, and it is a combination of availability, accuracy and acceptable user experience in all facets.  One aspect of operations management solutions which makes this expectation more challenging is that these solutions are inherently more complex – they include at least 2 software applications, sometimes 15 or more.  And complexity tends to reduce availability.

Several customers have asked how to practically achieve and sustain “trustworthy” operations management solutions.  An appropriate analogy is a fuel gauge in a car; if it is functioning less than 100% of the time, users won’t trust it at all.  The following are best practices:

• Design the solution to automatically handle many failure modes, including user error.  Most of the design of automatic teller machines (ATM’s) is handling failure modes.  Methods include automated workflow for missing or grossly erroneous data, software and machine health, network outages etc.

• Design the solution for some redundancy, including “store and forward” of data to withstand network outages and other failures.  Note that this technique is only usable when the software applications can rapidly process the restored data while processing “new” data.

•  Design the calculations for sufficient accuracy and availability.  Simple mathematics is much more available, but much less accurate, than complex mathematics.  Technology is available that delivers high accuracy and has built-in logic and knowledge to overcome many failure modes including “solver” errors, sensitivity to missing or inaccurate input data etc.

• Design the solution’s outputs using the “4 rights” instead of the “4 anys”:

1.  Information should be delivered at the “right” time (which might be earlier than “real time”) depending upon the operations management conditions.
2.   Information should be delivered to the “right” persons.  Operations management solutions tend to broadcast information including undesired performance and tend to broadcast information which is irrelevant to most users, which means that users must filter out information that seems like “spam” and users must learn to trust the solution.
3.    Information should be delivered in the “right” context.  There is an analogy which characterizes “data”, “information”, “knowledge” and “wisdom”, where “data” is raw data, “information” is trustworthy data (may include substitutions and reconciliation), “knowledge” presents a comparison of information to targets, constraints and similar information, and “wisdom” is prescriptive instructions to exploit desired opportunities and to prevent or minimize undesired conditions.

An operation management solution evolves technology is introduced, the operation evolves and as users increase their dependency and trust in the solution; the above methods are good fundamentals for the solution’s lifecycle.

A New Approach is Required to Enable It/OT, with Information Driven Systems!

Two weeks ago I wrote about IT/OT convergence, and some thoughts, while the convergence has been happening for years. It seems only lately that we running into the significant step of changing the organization from tradition structures to a modern / new generation Operational IT approach. But the interest in that blog post was significant, with many hits, and many direct emails on ideas, comments.

The fact that 4 significant companies I have visited lately that we find that the head of the traditional IT team, and strategy is someone from Operations, with limited traditional IT experience, but huge amount of Operational and Business experience. The strategies are now not about the technology they lead by an business/ operational value, and how do deliver solutions fast, and efficiently, with technology and systems that are sustainable, and evolutionary.

In the information driven space this is giving rise to a different approach:

Smart Plant a Realistic / Holistic View

Smart Cities, Smart Airports, Smart Farms, Smart Upstream Fields are all the talk, but when you get down to interviews with companies, cities etc, the definitions change from city to city, from major oil company to another, so if you looking for a clean definition it not to be found. But there are underlying trends you see across all of them:

Trends/ Objectives:

·         Faster decisions and less people monitoring / responsible for more. Leading to the Integrated Operational (control) centers.

·         Increased agility and efficiency through transparency across the whole landscape, so better alignment to plans

·         Increased Operational Continuity

·         Lowering of cost through increased understanding of operations, and operational efficiency of assets. Energy management and material management.

·         The Operational Workforce transition of experience and to a dynamic, digital workforce.

·         Environmental/ Safety and regulation control, limiting exposure and cost

·         Change of equipment/ instruments to “smart equipment” which have increased intelligence and “self monitoring” , a dramatic increase in data that needs to be understood, and used for more predictive awareness

Yes this is all a part of the Operational Transition I have been talking about, and believe will transform the industrial sector over the next 5 to 10 years, as part of the 3^rd industrial revolution.

But in the last couple of weeks we have worked with a company in Asia who has a really good grasp of “smart plant” and the overall concepts that need to addressed in their journey.

They are really looking at the 4 main themes with their unique names, but they also looking across these and how they interact, as well not just a plant but across assets.

This is built on their belief that Operational Workspace is changing and not in one area but multiple dimensions, with workforce change, but also ICT changes like “cloud," “Bandwidth," IOT (Internet of Things), Smart / intelligent devices, and the move to naturally using simulation.

The diagram below shows the two big axis they see changing, not too different to People and Asset changes we have seen before.

An interesting observation is the shift to “larger, more complex process” this is true in all industries, as the problem we are being asked to solve is significant compared with the traditional control, but the opportunity for return is significant as well. But with the use of centralized computing, and shared learning, the cost, and ability to solve these today over all size plants is possible.

In reality the fact that this company has engaged on journey and understands it is journey is important, understands the goals, and direction, the shift to manage “work” and transition their architecture to embrace “intelligent devices” so they can leverage the IoT developments and Big Data, Industrial Analytics. Probably means they will lead the transition and be positioned well in the new world beyond 2020, but we all entering this world!     

Operation Intelligence(Enterprise Manufacturing Intelligence) vs Business Intelligence (BI) the Difference and it are the time it be recognized!

So many times when I visit a customer site or discuss with product develops, or engineering houses people get confused over what are the roles of each system, and they must work in conjunction but they not the same. Especially when companies already have a business Intelligence strategy and tools, but they also have process analysis tools (trending) but let's move the focus away from engineers to the consumers of the information and their transforming role in achieving operational excellence.

The question of “why a company should implement an EMI solution if they already spent money on a BI solution. They already have the “slice and dice” and analytical ability within BI, so why waste money on an EMI solution?”

The realization is that users in the real time operations require empowerment capability to make decisions, to be able to access “trust worthy information” quickly and easily. Quickly seeing status of plant, operations, and easily been able to apply limited operational analysis to answer well known “Operational situational questions”. EMI and BI have different purposes, and they are aimed at a different audience. Manufacturing-specific reporting and intelligence are different in content, context and data frequency than the data in BI.

I had a long discussion with Gerhard Greeff (Divisional Manager: Bytes PMC, MESA trainer), on this subject, and he totally agreed in the miss understanding, that people have and how often they tried to use BI tools to build operational dashboards for operations and they do not get accepted or used. Also, this exercise results in significant IT projects to build the tools, and gather the data, so often to be far less effective that MS Excel, which many operational people will configure what they want. The requirement now is for consistency of information, and measures, causing a transformation in the market caused by “Apple” that time to access and value is far more critical than “perfection on information layout” introducing the concept of “good enough” will do. Like we do on many applications on smart phones where down loaded applications based upon a functional need, and have limited ability to change it, except the basic configuration, but it works and is delivering value fast.

You may be asking can you clarify the difference, so I have used some text from Gerhard’s paper in “The Mom Chronicles”.

“Data in a BI solution is typically at the same low frequency as that of the ERP system such as daily values. For a Plant manager that wants to know what is happening on a shift or hourly basis, BI will thus be inadequate. BI tools are typically not designed and implemented to take into account the real-time nature of manufacturing operations and its very large data rate. As such, BI are not able to handle the high frequency of data receipt and the required fast response-times of reporting/visualisation required by manufacturing operations.

Executives use BI as strategic analysis and decision-making tools for the company. From their BI systems, they can see the profitability of individual plants and sites and, as such, can make the decision to close down a plant or to change the manufacturing strategy. They typically work on confirmed and validated numbers and results as they want to ensure they have accurate data when they make the decision. These validation/confirmation or auditing steps often add considerable time between the actual event and the time the data end up in the BI solution.

Site-level production personnel however cannot wait for the niceties of auditing and validation before they take action. If a report or an EMI dashboard indicates that something is wrong, it is their responsibility to investigate and take corrective action. If a feed-rate is lower than planned, the production manager is not going to wait for the confirmed result in the BI system tomorrow before he takes corrective steps. No, he is going to investigate or have someone investigate for him. If it turns out to be a false alarm, then he is glad as it is a crises averted. If something is wrong, he takes corrective action, or at least knows and expects the bad results from the BI system tomorrow. Production executives hate surprises, even good ones.

EMI systems thus have a two-fold purpose:

1. To provide early warning in real-time for potential problems in order to make decisions or take action, and

2. To provide “slice and dice” data on historical data and Operational data for process improvement, and operational status, delivering the information in time, equipment, and operational context.

EMI has data available at the granularity and frequency delivered by the individual applications. This can be from seconds to days, depending on the specific operations requirement. The data is also available per individual piece of equipment, line or processing unit and can also be rolled up into hours, shifts, days or weeks for any of these. The granularity of EMI systems is closer to real-time, and they are often used as real-time dashboards for Operations Executives.

BI may be able to provide the historical “slice and dice” data, but typically, not at the level of granularity required by operations managers. BI will not be able to provide the real-time early warning required by the plant. Both of these are thus needed to support manufacturing companies adequately.”

The challenges vendors have is how to deliver this operational information in a rapidly consumable form, with minor time and effort outside of operations. The system will need to evolve, with more operational questions answered out of the box, or an experience which enables operational people to answer these questions.