Seven lessons for Industrial IoT and data teams
Source article by Dimitrios Spiliopoulos: Seven lessons for Industrial IoT and data teams: How to forge a path to success
In the Industrial IoT world, we often hear comments like “Let’s make our existing machine or tool connected, and later we will find the way to create value or monetise it”, or “we need more and more data so we can solve business problems”. Is this approach enough? Is it a good idea to start the thinking process from connecting the products and collecting huge amounts of data?
In the Industrial IoT space, data and IoT teams face challenges which have many similarities. This inspired me to write about some lessons for both the data and Internet of Things (IoT) teams of companies which adopt IoT services and technologies. We should not forget that data and connected products are like the two sides of the same coin.
The seven lessons for Industrial IoT and data teams are listed below:
Lesson 1: Start from the problem or need you want to solve, not with the solution
Lesson 2: Prioritize the implementation of IIoT projects
Lesson 3: Think big, start small, fail quickly (learn) and scale fast
Lesson 4: Break the silos of the company’s departments and data
Lesson 5: Explain the data with storytelling
Lesson 6: Empower, train and give exciting problems to your IIoT star employees so you can keep them during 2018
Lesson 7: Continuously apply all of the above six lessons