Why Fact Based Data is Critical to your Maximo Implementation

After attending Pulse 2013 you are overwhelmed with ideas and visions from every direction; Cloud, Security, Instrumented Assets, Analytics, Mobile, and Social Media.  Big data is a big priority for IBM.  In other words a Smarter Planet.  But it doesn’t take long to descend from the cloud, get back to where the rubber hits the road and to try to relate what all of that means to many of us just trying to implement the basics of Maximo.  Clean, reliable, accurate data is the single most important aspect of your EAM because your credibility and the credibility of your business depend on making informed decisions based on accurate data.  40% of all Maximo implementations fail because they are not rooted in objective fact based data.

Data that Matters
How many of us have been in the situation of defining requirements and we ask managers or users what data they want and invariable they say: we want it all, whatever the system can provide we want it. The better question to ask is:

What data drives the decisions and improvements that you need to do your job.  Having it all is a recipe for disaster unless you have multi-million dollar budgets, a business need, and the resources required to gather, secure, analyze, and act on large volumes of random data.   The more you want, the more it cost, and the more complicated it is to get it. Collecting data just for the sake of it is a waste of time for most of us.  Don’t load Maximo up with dirty data because it erodes system credibility and the trust of the users.  Less good data is better than more bad data. Of course that leads to the argument that one man’s junk is another man’s treasure.  Make sure that whatever data is deemed necessary is justified with a business case.  Just because you can, doesn’t mean you should.  Don’t do things that don’t matter. Bad data leads to bad decisions.

Business Process Re-Engineering
When you finally define the data that matters, you need to determine how you currently get that data into the hands of those that need it.  Relentlessly scrutinize your business processes and get answers to the following questions:  Why you do, how you do, what you do, and who does it?

Analyze how you can do this better and streamline your business processes to support the data you need and the way you get that information to the right people.

“Things should be as simple as possible, but no simpler”

Albert Einstein

It is important to simplify the user experience.  If you don’t, you won’t consistently get the data that you need. Remove road blocks and meaningless steps in your processes.  Don’t make users do things that don’t matter to them. “Make it work like I do” by using smart phones, tablets, and configuring Maximo to support the user’s work processes.  Optimize the technology to take advantage of pushing/pulling data from users, reduce double entry, make it easy to capture what was done, and access what needs to be seen.

Realistic Expectations
My definition of success is if results meet expectations.  Having realistic expectations about the data is very important to how you interpret the successfulness of Maximo delivering what you need.  For example, you want to capture labor and material costs on a work order:

Case A –

  • User enters whatever hours and materials they want on the work order

Case B –

  • Labor hours entered in a time/attendance/payroll system integrated with Maximo work orders to capture labor hours/costs.
  • Materials are charge to work orders via issues from inventory
  • PO materials and contracts are charged to work order upon receipt

Two very different expectations in terms of the data being captured and the degree of accuracy.  Don’t expect Case B results if your data reality is Case A.  Remember the more you want, the more it cost, and the more complicated it is to get it.  You have to decide how important the data is, how much it will cost to get it, and set realistic expectations.

Why is this Important?
Because everything discussed above provides the design specifications for your Maximo Implementation:

  • Data requirements
  • Business processes needed to support data gathering
  • User expectations of the results to be delivered by Maximo

“If you don’t know where you are going, you will probably end up somewhere else”.

— Sidney Heyward

This is the foundation, roadmap, and the requirements for designing and building out Maximo to support your business needs.  As you build and test, you compare the functionality against the requirements and expectations.  “Going Live” is the reality check and of course never goes quite like we anticipate.  All of us have to deal with the changing winds, rough conditions, and political currents of our work environment that are constantly trying to take us off course.  Don’t lose sight of why we use Maximo:

  1. Asset Reliability – if your assets aren’t running you are out of business
  2. Improved Efficiency – streamline business processes to gather data
  3. Command and Control – your success depends on making informed decisions based on accurate data

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About Randy McDaniel:
Randy has a B.S. degree in Mechanical Engineering from the California State University at Fullerton and has spent over 35 years in the field of maintenance engineering, maintenance planning, capital projects construction, and facilities maintenance. His industry experience includes oil refineries, petrochemical plants, universities, steel mills, assembly plants, lumber mills, and utility plants.

He has spent time as a Maximo senior consultant providing business process re-engineering assessments and managing Maximo implementations. A vocal advocate of Maximo, Randy has been the Chairman of the Southern California Maximo Users Group since 1998 where he often presents best practices, tips and other real life Maximo experiences.

Currently Randy is the Maximo System Administrator and Facilities Management Information Systems Integration Manager at the University of California Los Angeles. He manages the implementation of Maximo and provides IT integration direction and vision for the General Services business unit.

This post originally appeared on the Tivoli User Community boards on March 18, 2013, and is reprinted with permission of the author