How to build a cost picture for improving CMMS, EAM & ERP data.
The current state of your data: quality, completeness and quantity.
Setting goals for data improvement goals helps control cost
Industry sector and location’s influence on data services costs
How the brand of CMMS, EAM and/or ERP software can affect data management costs
Selecting the right data management services partner is the critical cost factor
Compare – In house vs. Traditional Data Processor vs. Sharecat Data Services
Data management is a continuous process
If only it was as simple as publishing a price list; unfortunately, it’s not a one-size-fits-all solution. The issues you have are ones that are common with many other operators across industries, but the state of your data, the goals you want to achieve, and when you need to do it is unique to your company.
For Sharecat Data Services, supporting you with a pre-defined and predictable fixed price model is not a problem, but to be able to do so, we first need to understand where you are now and where you want to be.
This guide will help you through the key items for you to consider when developing a budget for how to improve your data in your CMMS, EAM, and ERP systems in a cost-effective manner.
There are six key factors that will influence the costs of improving your data; these include:
The current state of your data: quality, completeness, and quantity.
What data standards have you applied, and how consistently you have used them.
The improvement goals you have
The industry and locations you operate in
The brand of CMMS, EAM, and/or ERP software (and version) that you are using.
The data management partner you choose.
Of these core variables, only one of them is an external factor that you can influence – the partner for data management services you choose.
Selecting the right partner has the biggest impact on the cost of data management services, whether cleansing, enrichment, standardisation, or cataloguing is required.
But, understanding what influences each factor can help you define a clear plan and scope for you to select the best partner to deliver effectively. The following sections provide further detail for each factor.
As mentioned above, for us to be able to define a fixed price model we need to know the state of your data and what the end target is. The end target can be simple to define in terms of a big-picture view, but the steps to get there, whether data cleansing, data strandardisation, data enrichment, or data cataloguing, depend on where you are now.
The first step for any customer is to diagnose the state of your data. With a copy of your asset and material data exported from your ERP, EAM, or CMMS system(s), we run a health check to define the snapshot of the state of your data as it is now.
Our healthcheck process includes automated validation and diagnostics together with expert review to define completeness and identify errors, duplicates, and inconsistencies. We then benchmark the state of your data to our in-house metrics and identify and recommend what issues to address in order to give you the biggest impact.
The healthcheck is summarised in a report, which can be used as a basis for planning and detailed budgeting for a data improvement campaign. It can also be used as an independent review of your current state.
This first step typically costs between $7000 to $11000 (USD) per health check. Note that this figure depends on the number of data exports/systems/instances that need to be evaluated.
Data cleansing is focused on identifying errors and duplicates and removing them (find out more at Data Cleansing). The more data you have, the higher the chances you have errors and duplicates, so having less data is actually a positive influence on reducing the cost for data cleansing (but a negative cost influence for the enrichment and cataloguing costs).
All of this assumes that you have a consistent data structure and standards applied to your data. If not, then it is an additional variable to consider when checking if the information is correct, but one that often happens due to assets having different ages and with multiple instances of an ERP, EAM, or CMMS within a company. The best approach to take here is to first define the common standard and structure to apply and then use that as the basis for evaluation and cleansing.
We also recommend that you identify which fields are the most critical as a group or groups; this is something that we can help you identify and define. These are the fields that are mission critical / give the most value from being correct, and/or have the highest risk if incorrect. By focusing on these fields first, you can optimise your cleansing scope and costs
Data Enrichment is focused on adding missing information to existing data sets that are partially complete (you can find more details here at Data Enrichment Services).
Defining the magnitude is simple and something you can do without support, as it is simply the number of fields in total that are currently empty for your existing records in your ERP, EAM or CMMS system.
From our experience, material/item masters in CMMS systems are typically only 20% to 30% complete, but you do not have to hit 100% to benefit from major improvement. As with data cleansing, it is worthwhile to define that fields are the most important generally, or by type of equipment. With these groups defined, it is then simple to focus on and measure the number of missing fields you have and to be more cost-effective in your data enrichment campaign.
Enrichment can also add a new field to existing data and populate the values, such as embedded CO2 footprint or UNSPSC identifiers and similar. These kinds of enrichment scopes are simple to define which is an effective approach for both cost and execution of the work.
Although the perfect situation is to standardise all your data so that it is harmonised with the same approach, it is often worth breaking up the challenge, which also helps break up the investment. By harmonising one facility at a time, the process can be tuned and optimised for each step while ending at the same final goal.
Data Standardisation gives major benefits to the effectiveness of the process being run in your ERP, EAM, and CMMS systems (as our Data Standardisation Services page shows). But, many organisations do not have a defined approach for data standards and structure or how to implement these in their systems and data. This is typically because their data has evolved over time in the same manner as their facilities.
If you are a company with multiple operations systems and even multiple instances of the same system, then the standards and structures of your data probably vary as well which can make it confusing on how to begin.
To address data standardisation in a cost-effective manner, we recommend breaking it down into steps:
Step 1: Identify what standards you have used as part of your data governance.
Step 2: Check your data to see how consistently your current standards have been applied (or not).
At this point, you have the overview of how standardisation has been applied to your data.
Step 3: Evaluate and identify the gaps in your current data governance standards. For example;
Step 4: Create a company-specific reference data library using the standards and initiatives that are relevant to you as the basis.
Step 5: Map your current standards to your new reference data library to begin transforming and harmonising your data.
We are a strong believer that to deliver standardisation this cost effectively requires working with a partner who understands your industry and the standards relevant to it, such as Sharecat Data Services. It is also worth using a partner, like us, who has a range of standard reference data libraries that can be used as a starting point to streamline the process and who can guide and/or work with your teams to adjust the reference data library as needed.
Here’s some good news, the simple answer is it doesn’t.
Data cataloguing is focused on processing new information efficiently to establish data records in your CMMS, ERP, or EAM system. This means that your existing data isn’t relevant, but having data standardisation and governance framework in place is extremely important and will influence the efficiency and quality of data cataloguing. Unclear, inconsistent and generic governance rules and standards often mean worse data delivered and longer time to process.
Having a clear data standardisation approach aligned with the needs of your systems enables the effective use of automation to speed up the processes for cataloguing new information.
Other elements that can reduce the cost are:
Clearly defining your goals of what to fix and in what order will help not only with defining and breaking up the cost, but it will also set clear targets and milestones to help achieve your journey to data strength.
Significant data improvement can be an achievable short-term goal if you tackle your biggest weaknesses first. From that point on, your focus should change to a continuous improvement and maintenance approach where you ensure all new information coming in is correct while, in parallel, you work on the remaining issues in your existing data, again in order of priority.
Which sector you operate in and the locations of your facilities affect the regulations you must consider as well as which best practices and data standards are most suitable for you. For companies with operations globally, you must take account of regional variations so that you can add to your core corporate data governance model as needed to meet regional requirements and also local work practices; this can be as simple as the difference between metric units in Europe compared to Imperial units in North America.
Software such as SAP, Maximo, IFS and STAR all provide comprehensive suites of functions, but are each different in their approach to addressing your operational processes. The software itself does not affect the cost of data management, but if you do not fully understand the software, you cannot effectively process information and deliver it in the correct format to be loaded.
The state of your data and what software you have in place are both largely fixed items. How you approach the data management tasks required is the main variable that affects cost and significantly influences your chances of a successful outcome. This means that the resource you use, whether internal or external, is the most significant element for ensuring you achieve your goals within your budget.
The following sections are designed to give you some guidance on what to consider when you are selecting a partner and explain the rationale of how Sharecat Data Services helps our customers so that you can decide whether we could be suitable for you.
It’s quite natural to think, “This isn’t rocket science; we can fix this in-house and save having to pay for external support,” and you’d be right. You should have a capable data management team internally. However, there is almost no chance that you will achieve your goals as fast or at a lower total cost compared to a specialist data services provider if you attempt to do it all yourself.
Specialist partners bring the know-how, processes, and tools to deliver the data you need at scale, faster, and at lower cost. They can also mobilise faster, scale up and, importantly, scale down with your needs. Avoid diverting internal resources and personnel away from operational needs and having an oversized data management team that is underutilized once major data management campaigns are completed, weighing on your bottom line.
Performing some work in-house is a good way to optimise external costs. If you are considering doing this, make sure it is clear which aspects you are considering doing internally so that the external service providers you are working with can advise where the optimal handover point is.
Some points that are worth keeping in mind when you’re evaluating data management services partners:
Excel does not count as “smart technology” for data management services. It is a great tool, and one we do use too, but processing large volumes of complex asset and equipment data for CMMS, ERP, and EAM applications requires specialist tools. Make sure you check with the partners you are talking to find out what tools they have and how they are used to ensure high-quality and consistent data is delivered.
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Your engineering contractors, service providers and suppliers are a key source of information, but you need to use them in the right way. Engineering contractors and suppliers typically do not use EAM or CMMS systems. They do not understand what is required and how it is required to be handed over for your operations. Ensure your team and/or your partner engage with your supply chain to help give guidance and improve the flow of information from your external partners and providers.
Beware of companies claiming that “generative AI/ChatGPT can fix all of these issues, no problem”. Generative AI is a powerful tool and has uses in parts of a data management process, but it needs structured data that is reliable to deliver reliable output. These are two things that often are missing in EAM, CMMS, and ERP data.
How do you want your data delivered? It is a small but important detail. Some versions of ERP, EAM, and CMMS systems require specific delivery formats, while newer versions also offer REST APIs for integrated data handover. However, although getting your partner to deliver directly into your system is the most efficient, you should consider whether this makes sense for you as an organisation, especially from an information security point of view. Always select a partner who is ISO 27001 certified (or equivalent).
Hourly rates are not an indicator of total cost or efficiency. The lowest hourly rate only incentivizes the provider to take the longest time. Instead, use the time with a partner to develop a realistic estimate including fixed or unit prices where practical to minimise unknowns and risk.
Does your data services partner offer a guarantee of the quality of their work delivered? If they are not willing to guarantee their work can you trust that they are able to deliver the high-quality data promised? If it’s not guaranteed, then you will have to pay for any rework to fix errors caused by your service provider, resulting in unexpected and unnecessary additional costs.
There’s a lot of information on these pages, so to help summarise the different approaches available and also to explain why Sharecat Data Services’ approach is normally the lowest cost and lowest risk option, we made a short comparison.
Let's take a closer look:
COMPARE DATA MANAGMENT PROVIDERS | In house team.png) | Traditional Data Processor |  |
|---|---|---|---|
| Keep your info in-house |  Yes |  No | No |
| ISO 27001 certified |  Possibly | Depends on provider | Yes |
| Inexperienced personnel | Possibly | Depends on provider |  No |
| Requires close follow-up |  Yes - in house management | Depends on provider | No |
| Divert internal resources away from other work | Yes | Yes | No |
| Required to train personnel | Yes | No | No |
| Understands information and data needs for your industry and locations | Yes | No | Yes |
| Specialist tools for data management | No | Depends on provider | Yes |
| Can provide guidance and recommendations for cross-industry initiatives | Possibly | No | Yes |
| Can provide cross-industry best practice | No | No | Yes |
| Familiarity with brand of ERP, EAM or CMMS software | Yes | Depends on provider | Yes |
| Clear-defined fixed price | No | No | Yes |
| Quality data guaranteed | No | No | Yes |
| Proven data management execution model | No | Depends on provider | Yes |
As you can see from the above, the only element that you need to accept when using Sharecat Data Services, is that you have to allow your data to be handled outside of your own organisation. This is why we are an ISO 27001 certified organsation and we are more than happy to be audited by customers for them to be comfortable that their information is in a safe pair of hands.
ERP, EAM, and CMMS data is not static – it changes, grows, and evolves over time. One-off data improvement campaigns make big steps forwards, but data strength requires maintenance; otherwise, you’ll end up back at square one. Maintaining data strength is much simpler and cheaper than periodic improvement campaigns, so we encourage our customers to also plan how to maintain their data once it has been improved.
If you have enough information and think we can be the right partner for you, then get in touch. Our team is ready to understand your needs and build a plan for how to address them.
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If you’re not sure, then we encourage you to read more, but we are also always happy to talk to give clarification and guidance.
ISO 27001 Certified