I recently came across articles in the Financial Times, WIRED, arsTECHNICA and other places about Google having built a quantum computer that beats the hell out of “traditional” super computers (although they aren’t that slow, either). Some are already calling it the “dawn” and the “supremacy” of quantum computing. Is the Terminator’s Skynet finally arriving in our homes? Not quite yet, I suspect…

However, as a physicist, these articles about quantum theory reminded me of some ideas that have been cycling through my tiny human brain for awhile. First, I need to turn back the clock of science a few years:

One of the most recent important milestones in the history of physics are the so-called “double-slit experiments” (https://en.wikipedia.org/wiki/Double-slit_experiment), which completely changed our thinking about the world’s true nature and became the basis for the new world of quantum mechanics. In the past, physicists tried to determine whether things (e.g. photons, electrons, atoms, etc.) are particles or waves: A particle cannot be a wave. A wave cannot be a particle. It’s either-or. This was the received truth for hundreds of years. Period.

Well, as you remember from school (I hope), the double-slit experiments led to the paradoxical but proven (!) result that quantum objects are both particles and waves.

Damn. This doesn’t fit in our binary system: 0 or 1? Right or wrong? Good or bad? Black or white? Yes or no? All or nothing? Yoda or Darth Vader? Well, you get it. ;-)

Matthias Horx, a renowned German researcher and futurist that I quoted in one of my early blog posts, suggests we should not deal with complexity by being afraid of failure, but by simulating, experimenting and – most importantly – training ourselves to recognize the value of “as-well-as”, instead of “either-or”.

This may sound academic and theoretical, but I will show you in a second why this “as-well-as” is so important when we aim to identify and harvest value from today’s IoT data masses:

Leaving your comfort zone and allowing yourself to indulge in a kind of “grey thinking” is the attitude you need when you start out on your IoT journey, because I often hear these self-constructed barriers to progress from our clients:

• Wait, there are still some quality issues in our data.
• Wait, there are still some inconsistencies.
• Wait, there are still some gaps.
• Wait, we do not anticipate 100% accurate results from our analytics.

This too-strong focus on achieving 100% accuracy is a major issue and hurdle in many experts’ brains: Let’s say you could exploit your “oh-so-bad” data to come to “only” 90% prediction accuracy for some blind spots you want to uncover in your grid, your infrastructure, or your assets. Why not take that 90% and use it, since you have to admit that today you might only be at 50% accuracy at max because – let’s be brutally honest – for some of these blind spots you are flipping coins and/or crossing fingers.

Take-away #1: Rejecting 90% because you cannot reach 100% is a bad idea. Something is always better than nothing!

Believe me, you will be surprised!

• The question is not if you should start.
• The question is when you should start.
• The question is not if we will find gold nuggets in your data.
• The question is how many we will find and how big they are.
• The question is not if we can generate value.
• The question is how much value we can deliver.

Well, and for those who still love the Yes/No-approach, I have some simple advice for you:

• No, your data is not “too bad”.
• No, your data is not “too little”.
• No, you do not need to clean up your data to find value.
• Yes, your data quality is good enough.
• Yes, your data sources are more than enough.
• Yes, our domain and data scientists will find “gold nuggets”.
• Yes, you will be surprised how much value we can generate.
• Yes, you get your money back if we do not produce the value we promise!

Coming back to the POC (Proof of Concept)/POV thing from my previous article:

• No, you do not need to do a POC to prove if you can do it.
• Yes, you should start with a POV to prove why you should do it.

Take-away #3: Some decision makers will always be looking for – and finding – excuses, if they do not want to put any effort into analyzing their data (I wrote another article about this last year, I think). But, if you are not just searching for excuses, and if you are really committed, three simple rules will help you to start harvesting value from in your existing data and your future IoT data:

1. Dismantle the “either-or” barrier in your brain!
2. Open your mind to thinking “as-well-as”!
3. Just do it!

Takeaway #4: In Austria, we have a saying: “You cannot be more-or-less pregnant”, because this clearly is a yes/no, either-or condition. But when it comes to IoT data exactly the opposite is true: You can have more-or-less value.

Think analog. ;-)

Of course, at this point I could start telling you about cost savings, improved efficiency, risk reduction, better maintenance, service enhancements, competitive advantage, new business models and new revenue streams – but I bet lots of vendors have already told you all that.

The question is: Did you achieve any of those benefits?

If yes: Congrats!

If no: Why not? Maybe you need to change your approach to what I am advocating here. ;-)

Well, you know how to contact me…