Sometimes, I feel that this is what I would say to myself about the data that we are able to track today. The data may tell you something you might not want to know. If you are on the quest for increased asset performance, moving into the IoT world, or trying to move up the maintenance maturity continuum, you absolutely need to know what the data is saying.  You need to hear the truth so you can take the appropriate action.  So, how do we do that?

Are you making decisions based on gut feeling or data?

When I was a kid I loved building things. Both of my grandfathers were big influences of mine in those early days, and I was always asking them questions.Thinking back on their answers, I realize now that it was all about data and experience. 

In one case we were building a model sailboat out of scrap wood and I asked what would happen if we put the mast more towards the back of the boat.  “Not sure” was the answer.  We didn’t have any data or experience building sailboats to draw a meaningful conclusion from.  So, we tried it.  We launched the boat with a line attached to it and it didn’t work very well.  It only went in circles due to the forces on the back of the boat.  If we knew what would happen based on empirical data, “The Truth”, we would have come up with a different plan.

How many decisions do we make in our day-to-day and work life without the right data, or how often do we NOT want to know the truth our data contains?  How many of those decisions turned out the way we, or others, expected?  Sometimes we make decisions based on our instincts, or gut feel.  However, today, we have so much information at our fingertips, we should be using it to make better decisions. 

My wife and I had a heated discussion the other day because I missed a turn.  Sure, the maps application on my phone was telling me to turn in a mile, ½ mile 200 yards, recalculating.  If only I had the volume turned up, I would have heard it.

As W. Edwards Deming said, “Without data, you’re just another person with an opinion.”

Outcomes Aligned with Objectives

We all know that “hope is not a strategy”, but we often continue to use hope in explaining desired outcomes. We should be focused on the information and data we have readily available so that we can track and ensure our objectives can be met. Sounds simple enough, right? 

Lack of visibility can be a hinderance here. We may be collecting the right information either automatically or manually, but can we see it in a way that makes sense and helps us improve our decision making process. 

I've always worked under the notion “if you don’t measure it, you can’t improve it”. This should be etched in stone and given to everyone entering the work force no matter what your role is. 

If you set an objective for the organization, everyone should know:

• how it will impact them
• how they will impact it
• why its important
• what the outcome will look like

When we are heads down getting the work done, sometimes we don’t look up and see how our actions impact the organization and its ultimate goals. It's leadership’s responsibility to make sure everyone understands their role and how they fit into the bigger picture.

Data Quality

Data Quality is the condition of a set of values of qualitative or quantitative variables. There are many definitions of data quality, but data is generally considered high quality if it is fit for its intended uses in operations, decision making and planning.

How is the quality of your data?  Do you have a data strategy identified? 

I always get a lot of sighs and groans when we start talking data.  You would figure that in this day - when we have the ability to produce mountains of data - that our data would be much better than it is. The problem is, what we are collecting is not always aligned with our objectives, and may not be structured properly. Garbage in equals garbage out, right. There are ways to ensure you are capturing data correctly. I'd be happy to walk you through that.

Data Confidence

Data Confidence, on the other hand, is the level of trust an organization can place in data based on characteristics such as System and Process Integrity, Completeness, Currency, and Governance.  In other words, I may have the data to measure specific points, but does that data support the decisions I must make against the established objectives.  If I am trying to improve planning effectiveness and the quality of the data I have is good, that should equate to top shelf metrics.  What if I am not capturing actual hours on my work orders?  I would have no confidence in the ability of my data to provide an accurate indicator of the effectiveness of my team’s ability to plan the work. This is a common problem.

As W. Edwards Deming said, “In God we trust, all others must bring data”.  Make sure your folks are collecting the right data based on the KPIs you need to support your objectives.

Conclusion

The data that can be found in our business systems is what it is. If you find yourself spending a lot of time massaging data than you need to consider making some changes.

With the data we should be able to:

• Visualize it in a way that helps us make sense of the data, patterns, and make decisions
• Align the outcomes of our business processes, proven by data, to our objectives 
• Act on behalf of the data. Use it to make decisions and improvements within the organization

Visualize. Align. Act. This is the three step system that makes up our performance management philosophy. 

Bridge the gap between Strategy and Execution by aligning your objectives, processes and data to ensure the KPIs are relevant and usable.  Trust your data which may require a better understanding of your data and possible cleansing.  Identify targets and expectations and capture baseline information to support trending. Use the information to take meaningful action instead of merely posting reports.

Until then, turn up the volume on your navigation app and your data so you don’t miss the next turn.