SAG_Twitter_MEME_IoT_7_Ways_to_Win_June18The Internet of Things market is showing early signs of maturity, but there are still many projects that stumble*.

Implementing an IoT project is hard, very hard; many projects are complex, with many stakeholders involved - and if you cannot capture business value with IoT technology, then the projects are doomed to fail.

In the past few years the IoT has been greatly over-hyped; hence many IoT vendors had to convince the market of their pedigrees by touting use cases and customer success stories. In reality, IoT was only getting traction in very few markets - manufacturing being one, with the rest trailing behind.

There are a few indications that the IoT market is maturing. First, we see the number of platforms consolidating. Second, we see more respected analyst firms coming to terms with what IoT platforms are supposed to be and consequently ranking the platforms. Third, customer use cases are becoming available in abundance.

So now it is time to move from the convincing stage to the education stage, sharing first experiences of what works and what doesn’t - and where to focus to start your IoT or IIOT journey. Although the reasons that projects fail are many, there are some traits that successful projects have in common. Taking the lead from Stephen Covey, I like to call them habits – and I have identified seven. Taken one-by-one they are not revolutionary – but together they are powerful.

Based on my personal experience in the last years with numerous IoT opportunities and projects across the globe, the habits are:

  1. Lead with use cases
  2. Work in multi-disciplinary teams
  3. Put the platform at the heart
  4. Work backwards
  5. Be obsessed with analytics
  6. Plan your business continuity
  7. Develop your secret sauces

Although some of these might sound a bit cryptic, never fear; in my upcoming blogs I will dive deeper into each habit and give further insights in why some companies continue to deliver consistent success in the domain of IoT.

*First published in Big Data Quarterly.

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