8 Steps to Jump Start Digital Transformation
John Todd, Sr. Business Consultant/Product Researcher, Total Resource Management (TRM)
Posted 2/11/2025
TRM has been helping clients transform their maintenance and reliability functions by leveraging the many digital tools and solutions that have been present. As such, we have arrived at a method that can help you define where you are going and how to get there. Here are our 8 steps to jump start digital transformation:
- Establish business justification
- Assess Asset Management processes
- Establish Scope and Tiger team
- Close data gaps in Asset hierarchy, spares, inventory
- Improve Job Plans
- Refine PMs
- Conditioning Monitoring/Anomaly detection/Prediction
- End-to-end work management lifecycle
Let us look at each one of these, in the light of an asset that is critical to your operation, yet you believe it is underperforming. We can glean out the nuances that may help you not only form the project, but also understand where you might need to end up.
Business Justification
Ideas from your team may seem like good things on the surface and everyone loves technology. But unless the result benefits the organization, they should remain on the dry erase board. The moment after the idea is presented, someone needs to ask how the idea will save or make money. Or, in some cases, greatly assist in complying with regulations and other necessities of your industry. If you can posit that a change in a process will reduce a cost by, say 5%, and if 5% of something is significant, you might have a candidate.
The changes that result from a digital transformation project need to be tangible and truly impact the way people go about their daily work. The term return on investment (ROI) may come to mind, so be prepared to come up with defensible numbers to convince those who are stewards of the budget to make the move.
For the underperforming asset, you will need to collect data that supports or refutes the assertion that it is not performing to expectations. This data may come in many forms, but it needs to be complete enough for you and those who are reviewing with you, confidence in the values and trends it is displaying.
One client that comes to mind had a set of 3 machines with an average Overall Equipment Effectiveness (OEE) of 85% and they knew they could do better. While the operation was profitable, there were many inefficiencies in the maintenance approach to the equipment and a recent labor cutback that both set the stage for trouble in the future.
The client had a couple of initiatives started such as vibration testing, inspection form creation, and a root cause methodology that did have positive impacts, but only in small (and even invisible) ways since they were not part of a larger plan. With a focus on a larger transformation plan, including how data was collected, how work was planned and scheduled, and the creation and maintenance of KPIs, in just a single year the OEE went up to 90%. While this seems just a few percentage points, the profit increased $3 million directly due to the increase in OEE.
When considering a jumpstart project vs. a larger scale digital transformation project, it is important to focus on a subset of equipment, not the entire inventory across the organization. A jumpstart project is used to prove the return on investment quickly which results are then used to build the case for a much larger project or series of projects.
Further, a goal of any improvement project is the notion of “self-funding.” The funds saved by implementing the project can be repurposed for further improvements. If a 5% savings results in a 1% expenditure on the project, then the improvement project certainly funded itself. If the results are a wash, then perhaps the improvement project was not as well thought out as it should have been.
There are also many potential indirect savings areas that can be significant. Savings such as:
- Inventory holding costs
- Improved utilization of labor
- Reduced overtime
- Reduced contract labor costs
- Expedited shipping costs – these can be huge!
- Reduced material handling costs
Functionally there can be even more areas of savings because of digital transformation. Consider the following:
- Dramatically reduce the need for emergency maintenance
- Greatly improved productivity by implementing mobile solutions
- Optimization of preventive maintenance activities reduce spare parts costs
- Equipment life extension, even if only be a few years can be significant savings, increasing the ROI of any project
- Liberate key staff to focus on strategic activities vs. mired in the daily tactical
Some of these areas expressed in a table:
| Area of savings | Ranges |
| Reduce Emergency Maintenance | 80-90% |
| Labor productivity | 10% |
| Optimize PM activities – Labor | 50% |
| Optimize PM activities – Spare Parts | 20% |
Contributors to the ultimate ROI of the digital transformation project will vary from one client to the next, as will their relative impact. It comes down to the efficient use of the budget to carry out the goals of the organization. Cutting cost(s) is not the answer as that leads to backlog and equipment not being cared for as conditions dictate. Rather it is the correct expenditure of funds and the time of individuals where returns are the most valuable.
One final note on developing the business justification is the impact the transformation may have on the collective bargaining agreements in place between the organization and any Trade Unions. If new processes and ways of doing work have a material impact on the scope of tasks per the agreements, there may be a need for discussions and amendments.
Assessing Processes
Once the business justification has been set, it is a best practice to assess where the organization is, not only with managing assets, but with any related processes. This can be a big task because it goes beyond just looking at maintenance processes. Operations, inventory, accounting, safety, quality control, etc. can all play a role in how assets are managed. Don’t just look at one area of the business to go digital… consider a wider scope.
When TRM assesses an organization, we look across disciplines, for example:
- Fundamental maintenance and related discipline process(es) health
- Equipment procurement
- Management/Supervision team(s)
- Relevant/related policies and execution (Safety, Training, etc.)
- Improvement initiatives (Current and past)
- Staff skill levels and growth
- Approach to work planning and scheduling
- Work prioritization and categorization
- Approach to preventive maintenance
- Use of condition monitoring and/or prediction
- Spare parts management (inventory and delivery)
- Availability and confidence in related technical information (Bill of Materials, manuals, etc.)
- Root cause and Risk mitigation programs
- Overall time usage/efficiency
Assessment can be uncomfortable. Your first impression is that the results will tell you everyone and everything is wrong. You will find that you and your teams are doing many things very well. Yes, there will be several gaps… some quite large, but overall, you are all professionals and in general know what you are doing. Look to these assessments to gain insight into how other organizations are doing similar functions and glean from them the good stuff to see how you might implement it.
Be sure to consider the underperforming asset as part of the assessment. Do not leave it out because you know it is an issue. Rather, assets with less than stellar performance can be excellent signposts, pointing out problems in a process.
Returning to our client with the 5% increase in OEE, the assessment exposed the need for clear definitions of routes for the various disciplines. Lube techs, mechanical, electrical, and instrumentation engineers did not have regular patterns nor guidance as to what to capture while inspecting the equipment. Developing failures would be missed, and some areas of the equipment were over-inspected. Developing these clear routes, focused on the skills and scope of the various maintenance disciplines, had a direct result in increasing the reliability of those 3 machines.
Establish Scope and Tiger Team
Someone with authority needs to own the transformation. For projects so widely reaching as digital transformations can be, there needs to be a sponsor who is there from day one all the way through to the end. The sponsor might not be there every day or meeting, but they are very involved and visible. They are the ultimate tiger team leader. Decisions that require their level of involvement are expected to be made quickly and concisely.
The tiger team who is tasked with executing the project needs to have time dedicated out of their day to do what is needed. It is short-sighted to think that you can just add this task to their already busy day and expect efficient results. If they are creative, they can relegate some of their daily tasks to automation or other digital tools, freeing up time for the project. Digital transformation has already happened!
Who should be on the team? The answer is not as simple as you think. Certainly “everyone,” is not the right answer… yet “everyone,” will need to be involved in the transformation. While there may be a core team who has a significant percentage of their time allocated to this project, there will be many other people on the periphery who will be involved. From the beginning, knowing how far outwards the project will reach is important.
Roles (staff and management) such as maintenance, reliability, operations, IT, warehousing, transportation, purchasing, contracts, and even accounting will have a vested interest in a transformation project. Avoid the unpleasant surprise of a newly minted maintenance process that runs up against a best-practice accounting principle. Each role brings specific experience and knowledge that is unquestionably valuable. Cast a wide net when considering who in the organization will participate.
The scope of the project is important. While it might be an aspiration to go digital across the organization that might not be feasible in the short-term. Have everyone, including the sponsor, agree to the scope of the project and what the next areas of improvement might be. Nothing wrong with a phased approach. We do this area first, then next year we do this one… etc.
Let us not forget about the Organizational Change Management (OCM) and training aspects of this significant project. There are many structured approaches to OCM, ADKAR (Awareness, Desire, Knowledge, Ability, Reinforcement) is one such approach TRM adheres to. In many organizations, OCM is more of an internal function than of an implementation provider (IP), but the IP may play a significant role in providing information and training during the project lifecycle. The goal of the OCM element is to facilitate lasting change, in this case a beneficial digital transformation of the organization. Effort will need to be spent to manage the change in the long term, not just for the duration of the technical project.
Part of the OCM process is the need for hands-on training and even coaching for staff. If staff are not given the time to absorb or even explore the changes afoot, they can easily become frustrated and return to their previous state. Training needs to be designed, just like the solutions they use, to reflect their daily activities. Staff needs to understand the “why” behind each field they are expected to fill out. This level of understanding is only possible with a thoughtful approach to training under the OCM umbrella. No one knows your staff better than your staff does.
Back to focusing on the underperforming assets may be the complete focus of the project. If their lack of performance is significant enough, then efforts to transform the way they are maintained or operated may have significant value.
While the 3 machines for our example client were huge and sophisticated, and the most important for their operation, focusing on them vs. “everything,” in the operation enabled those involved to stay on track. An estimation as to the criticality of the equipment to the operation is an important concern while forming the project scope. It could be argued that “everything” is critical, otherwise why would you own it. But the equipment that is generating revenue each day is perhaps the best set to begin with.
Close Data Gaps in Asset Hierarchy, Spares, Inventory
More than likely the assessment mentioned earlier will point out gaps in the areas of asset management and the supporting roles such as inventory, purchasing, and operations. No one does all these completely well. There is a lot to consider and many moving parts to get the right parts to the right people at the right time.
There will always be low hanging fruit within reach. You may be surprised at the value of adding a field to a record in a software tool your team uses daily. This simple field with the information in it that they need all the time can have a huge impact on their efficiency. No more emails asking for information… it is right there on the screen.
These activities will take effort. Bridging the gap between what the equipment consists of and what is in stock to support it will take someone physically verifying any differences. A model number from years past might not support the use of recently received spare parts, and vice versa. Physical verification of spare parts on the equipment and physical inventory counting will be necessary. Equipment exploded views, spare parts lists, and other documentation from the manufacturer (or the design team) can be invaluable. Yet, documentation can be filled with superfluous information that can cause distraction. An experienced team, whether in-house or contracted, will be able to make use of all sources of information.
Ultimately, the collected information: new spare records, new parts lists, new procedures, etc. need to have a visible home in the “technical database,” the operation is relying upon. Modern CMMS/EAM/APM systems are well suited for this record capture activity. Then, once the data is entered into the system, an official process needs to be put into place to maintain it over time. Responsibilities, as well as enablement and training must be in place to ensure the information continues to serve the organization well into the future. If data is not maintained it grows useless very quickly.
For the underperforming asset, closing the gaps in where it resides in the hierarchy and the availability of spare parts may be all that is needed bring it back into health. The asset itself may not be the cause of the lack of production, rather it is all the processes around it to keep it healthy that are not performing that may be the hinderances. This in part was the case with our example client. They had an 88% correctness in their inventory counts, so there was room for improvement. Improving the accuracy of spares processing and storage greatly assisted daily work planning as well as the confidence in shut-down pre-planning.
Have your team draw out their top 3 daily processes and take a hard look at each step and role buried within. You might be shocked at how many hoops they must jump through just to hand a part to a technician. Every process has some hard requirements, but many “steps” may exist because of conflicting goals that each role in the process may have. Use this process review to break down the barriers!
Improve Job Plans
Job Plans are the typical guide to what your team does for specific work. Some may be high level while others may be very detailed. Part of the digital transformation is to make sure records such as Job Plans are updated and efficient. The goal is to be sure these plans are made appropriately digital so that they can then be managed well. You may already have quite a number of these records but might be lacking a review and update process. Don’t just throw them out but rather have your team look at each one to ensure the steps and items needed to perform the tasks are complete.
What then are the elements of a “good” job plan? While job plans can vary depending upon the scope of the work at hand, the following is a list of elements to be considered to implement in the job plan refinement activity:
- An alphanumeric and referenceable identification “number”
- A clear description of the overall work to be performed
- A revision number to ensure only the most current is used (and an official process to maintain version control)
- A status (example: DRAFT, ACTIVE, INACTIVE, etc.) to also ensure only the correct job plans are used
- An estimation of the overall Duration of the work
- Does the work require downtime?
- Does the work require permits, special skills, safety considerations, etc?
- For each Task in the job plan:
- A clear description
- Who (specific person, skills, craft, etc.) should perform the task?
- Estimated time it takes to perform the task.
- Any materials or spare parts needed to perform the task?
- Any outside services (contractors) needed?
- Any special tools needed?
- Indication or relationship to equipment where the job plan is applicable or not
Job plans that have been formed with these elements in mind become invaluable as they come alongside the preventive maintenance, route, inspection, calibration, and general work activities. Field teams can have confidence in the direction they are getting from job plans, knowing that there is a feedback mechanism available to them to provide input for refinement over time.
If the task lists for the teams maintaining the equipment are incomplete or simply misleading, the likelihood of an asset underperforming is quite high. Failures can be easily introduced via incorrect maintenance procedures. Even the order in which tasks are performed may be critical and if done incorrectly, the asset suffers.
An important element of any transformation project is data cleansing before implementation. If you are implementing a new system (for example a CMMS or EAM) or are upgrading to a current one, it might be a good opportunity to cleanse your foundational records and archive the years of documented work results. You do not want to hear the same complaints of “bad data” in the new system as you heard before with the old. It will take significant effort, but there are tools and techniques available to help cleanse the data, so your new system starts fresh and relevant.
Some of these tools may be inherent to the database(s) you are currently using. Extract Transform and Load (ETL) is a well-used term, but it still describes the process. No matter the current system or database, bot the foundational data records (such as assets, locations… those rather “fixed,” records) and the transactional (years and years of history in records such as work orders), will need to be extracted. These potentially millions of records will end up in an interim database or series of spreadsheets for the next step.
Transformation in many cases might not be necessary or be very limited. If the new digital system is similar in structure, then only a few elements will need to change. If the old system is using old storage methods, then significant transformation of the data may be necessary. TRM uses several commonly available and custom developed tools to assist with this process.
The loading process is rather straightforward if the transformation step has been performed with the result and final system in mind. Snapshots of the data are taken to ensure the most recent transactions are reflected in the new production system.
Refine Preventive Maintenance (PM) Approaches
PM has always been largely focused on time. “We do this task every 6 months whether it needs it or not. If we don’t think it needs to be done, then we cancel the PM work order and wait for the next one.” Sound familiar?
Overall relying upon time to tell you which assets to execute a PM upon is not wrong, but higher levels of precision are possible. With modern equipment by default transmitting telemetry from sensors to computing systems, the usefulness of the calendar goes away.
Have your team take a hard look at the calendar-based PM activities and see how they have been of benefit over the years. Have they truly prevented significant failures? Is it hard to tell? Question your preventive maintenance approach to your equipment and see where it may lead. There is no doubt that, like Job Plans, having an efficient and focused preventive maintenance approach for all the assets will bring those that are underperforming into alignment with expectations.
It is not uncommon to see reductions in labor costs by 50% and spare parts costs by 25% with a judicious review and refinement of preventive maintenance activities. Adjusting the frequency and scope of the typical PM can have very visible and immediate results. With the advent of Artificial Intelligence, tools are being developed to further refine PM activities, taking in vast amounts of data and making suggestions for improvement.
Condition Monitoring/Anomaly Detection/Prediction
Vast advances have been made over the last 20 years in equipment monitoring technology. Nearly any piece of equipment, in any environment, can be monitored remotely. Every fraction of a second, huge amounts of data can be visualized. Averages, minimums, maximums, on and on the list goes. The key is knowing how to take advantage of this data to make decisions with. Software solutions exist to not only help you make sense of all this new and detailed data, but to also find nuances and patterns that humans might not be able to detect.
Once you are using actual condition data from and about your equipment, the organization can step into the world of just-in-time and predictive maintenance. It may be discovered that extending out an oil change based upon the usage of the equipment to 9 months vs. just making the change no matter what every 6 months can have huge financial impact. Remember that ROI we talked about in the beginning?
Condition monitoring has another impact that might not be immediately apparent. If an asset is monitored in such a way, it may always perform as expected. As telemetry is received and analyzed, trends can be seen, and failures headed off. Having this degree of insight into what the asset is doing now, and perhaps how it will behave in the future can be very valuable.
Here is a list of commonly available data elements that common sensors placed on and around the equipment report to a central “historian” database for further processing:
- Temperature
- Vibration
- Pressure
- Revolutions
- Actuations
- Run hours
- Levels (fluid, charge, output, etc.)
- Turbidity
- Oil (or other lubricant) condition
- “Leakage,” rate
- Operational status (open, closed, up, down, etc.)
- Failure modes
- Ambient readings (Temperature, pressure, etc.)
A good first step towards taking advantage of condition monitoring is to evaluate how much and what type of data you may already have from the equipment. In general, the Operations team has systems with this data already in place. They are using it to operate the equipment, not necessarily to evaluate performance or make decisions about the future. Given the right analysis and prediction tools, this data, which is growing every second, can be quickly used to gain insight.
This needed foundation of near-real-time data is most likely already in place. What will be new is the analysis of this data for insights, risk mitigation, and eventual decision-making. This data can also be used to paint a picture of how the equipment will perform (or not!) in the future.
More advanced approaches that use this same data are Anomaly Detection and Failure Prediction. To goal of these approaches is not to add to the long list of alarms the Operations team deals with all day. Rather, tools of this nature send alerts for humans to consider what is to be done over a longer period.
Anomaly detection uses proven statistical methods to look at the incoming data streams (from perhaps multiple sensors) to determine if the data is in statistical control or not. If an anomaly is detected, an alert is sent for disposition. Models can be trained to ignore anomalous events such as shutdowns or start up periods that produce known spurious readings but are fleeting. Since this analysis is occurring in real-time with real data, reviewers of alerts can have high confidence that the anomaly has value looking into vs. yet another alarm to ignore.
Failure prediction is the next step where machine learning and artificial intelligence come into view. Given those same streams of telemetry, these tools are trained to look across the data, seeking patterns that lead to failure… well before the actual failure could occur.
In general, failure prediction begins with 6-12 months of captured telemetry for the models to learn from. Then, given recorded corrective work, the model can understand when a failure appears to be brewing just by analyzing the training data. After training, the model is exposed to the real-time data streams, looking for similar patterns.
When a pattern is developing, the tools send an alert with a confidence level for humans to review and act. It is not uncommon for tools such as these to predict failure 1-3 months out. Of course, as conditions change, the models can be refined/retrained to ensure they are always looking for what is important to the operation.
End-to-End Work Management Lifecycle
Replace the phrase “work management” with any process set that your organization is digitally transforming. Armed with a clear picture of where the gaps are, the opportunities for digitization, more efficient processes that everyone agrees to, and the tools (including software) to make DT happen, you will implement a new or refined solution that moves much of what people do during the day to a digital platform. No more lost hand-written sheets or scrambled spreadsheets. Rather, consistent and understandable data, seamlessly captured and available for decision-making.
End-to-End Work Management Lifecycle
Replace the phrase “work management” with any process set that your organization is digitally transforming. Armed with a clear picture of where the gaps are, the opportunities for digitization, more efficient processes that everyone agrees to, and the tools (including software) to make DT happen, you will implement a new or refined solution that moves much of what people do during the day to a digital platform. No more lost hand-written sheets or scrambled spreadsheets. Rather, consistent and understandable data, seamlessly captured and available for decision-making.
A final caution: If you do not take a thoughtful approach to the scope and approach you take to make the transformation you might not complete the project. Go all the way back to the first step we are suggesting… assessing where you are at and what your goals should be. Start out right and the result is far more assured.
Wrap Up 8 Steps to Jump Start Digital Transformation
Elements of this article are examples from real world improvements that we can help you achieve with our unique combination of technology and maintenance and reliability experts. Every client is different with different goals and starting points. What is common across all is the desire to improve and get the most out of the resources the organization has available. These resources are People, Processes, and lastly Programs (technology). Taking a wholistic view of a digital transformation project leverages what you have already, removes barriers, and delivers flexibility for the changes of the future.
TRM has been working with clients for many years in many different industries and government, so we are well suited to understand your situation. Contact us to see how we might help you with your digital transformation needs.
Originally published with Total Resource Management
John Q. Todd
John Q. Todd has nearly 30 years of business and technical experience in the Project Management, Process development/improvement, Quality/ISO/CMMI Management, Technical Training, Reliability Engineering, Maintenance, Application development, Risk Management, & Enterprise Asset Management fields. His experience includes work as a Reliability Engineer & RCM implementer for NASA/JPL Deep Space Network, as well as numerous customer projects and consulting activities as a reliability and spares analysis expert. He is a Sr. Business Consultant and Product Researcher with Total Resource Management, an an IBM Gold Business Partner – focused on the market-leading EAM solution, Maximo, specializes in improving asset and operational performance by delivering strategic consulting services with world class functional and technical expertise.
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