If you like shiny new gadgets, an Energy and Utilities trade show is usually a sweet shop designed with you in mind. But just because it’s tempting doesn’t mean it’s good for you.
I hear so many tales of woe when I go to these shows. Things like control engineers having to look across ten different systems just to work out where an alarm came from or utilities paying vendors for access to their own data. The point is: that the tech sugar rush never lasts. And you’re often left with a bad taste in your mouth.
The biggest problem is that buyer’s remorse often leads to repeating the original mistake. When you’re feeling frustrated, the sweets look even more tempting. Maybe one more dip in the jar will fix it? But, actually, buying more devices and data services just deepens the hole you’re already in.
Annoyingly, it probably wasn’t you who dug the hole. It’s amazing how often these technologies make their way into the organisation before the data team(s) are even told. But regardless of origin, if you’re responsible for data architecture or data management, it’s probably your job to sort this problem out.
So what can you do? In our experience, there are some steps that nearly always make a big difference.
Think of them as the start of a healthier technology diet:
Make the organisation take a pause if you can. Getting procurement and senior leaders on side is usually the critical first step. You can’t plot a healthier future with a mouthful of sweets. Try to make this pause last long enough for you to mobilise and complete steps 2-5. It’s not the easiest conversation, but if you explain to people that they are about to waste their money, it tends to attract their attention.
Share what you have. What measurements are recorded by what devices, how often, in what formats, and where are they made available? What systems and points of integration already exist? Your organisation probably already has a lot more data than most of your colleagues think. They may not know it, but their impatience may well be about their access to data, not whether it exists. Share those insights with them, and use that goodwill to ask for their continued patience. Explain that more is coming. Then….
Bring data together. Define a data model that standardises and conforms to the presentation of data from different devices. Then, acquire all those different sources into a data repository or platform and align the data to that data model. The point here is that you are not measuring new data; you are giving the data you already have the comparability and supporting context to make it useful. Which is probably what everyone has wanted all along. Only they didn’t know it at the time.
Abstract away complexity. Present the enriched data you’ve created to end users in a way that removes the underlying movement and complexity. Create the capability to do the hard yards of data acquisition and transformation for them. Then, your (no longer frustrated) users can focus on their jobs. You have also now established control over the integration and presentation of device data. In your enabling role, you stand between the users and the value they are after. This should make it easier to hit that pause button in step 1 if you ever need to again.
Work with end users to extract everything possible out of the new information you’ve created. Until you and your users have worked with it and explored it, you won’t really know what’s missing and whether (if any) there are gaps in your existing device estate. If there are gaps, great, go and plug them. If not, also great, no more unnecessary expenditure.
The point here is that you can’t just buy insight off the shelf. This might not solve your sugar cravings, but very often, money is better spent on integrating and making sense of the data your organisation already has. This isn’t a particularly bleeding edge or technical proposition, it’s common sense, and best practice put into a few structured steps. Where most organisations fail, in our experience, is that they buy technology first and then try to work out what to do with it. They don’t have a pattern or a method to allow them to work out what they need first or deliver value when they’ve bought and installed it.
Transformative change can only happen when insight extends beyond specific process points or moments in time. Fundamentally it’s not the product of plug-and-play devices or the latest analytics tool the hype cycle has thrown up. It’s about creating a method for acquiring and presenting monitoring device data that spans the entire data value chain, with an overarching purpose and point of control. If you can get that right, the techie sugar headache should fade away.
Joe Horgan is a Senior Consultant at The Oakland Group
