Quelles données la société doit-elle capturer, sécuriser et analyser pour tirer pleinement parti de sa solution ?
L'article « How Smart, Connected Products Are Transforming Competition » (Comment les produits intelligents connectés changent les règles de la concurrence), publié dans l'édition Harvard Business Review (HBR) de novembre 2014, identifie les dix choix stratégiques que doivent faire les fabricants pour exploiter pleinement le potentiel de l'IoT.
Jim Heppelmann, PDG de PTC et co-auteur, explique le cinquième choix stratégique, expose les données que la société doit capturer, sécuriser et analyser pour tirer pleinement parti de sa solution, et prodigue des conseils pour vous aider à sauter le pas.
Now, keep in mind there's a variety of data that's available, and can be processed in conjunction with smart connected products.
There's external data coming from external data sources that might be available as sources through the Internet.
There's enterprise business system data coming from your CRM systems, your ERP systems, from the systems that you use in engineering, in manufacturing.
And then there's data coming from the smart connected product itself, so product data is fundamental to value creation, and competitive advantage.
But companies need to consider some of the key costs.
First there are hard costs. Costs like sensors to capture the data, or data transmission fees if you're pushing the data across cellular networks for example. And then all the storage required in the Cloud.
The second cost is the security, and privacy, and risk mitigation around that. Anything that's connected becomes a target of hackers. And you have a responsibility, quite frankly, if you collect this data to take good care of it, and protect it.
And then finally there's a dependency to have the right set of skills and infrastructure to perform analytics and to actually get value out of data that you're collecting.
So we think you need to start with your strategy. For example, a strategy that's focused on product performance might need to analyze data in real time in order to optimize products or to prevent product downtime. On the other hand a strategy that's focused on expanding into a system of system is going to need to be able to collect many kinds of data from many different sources which would potentially drive the volume and the variety up dramatically.
So our recommendation would be to start small, and try to document what are the specific use cases across your enterprise where you can generate real value. It might be automating consumables or dispatching service technicians or performing predictive maintenance and remote diagnostics. Think through those use cases, and try to document the data that would be required to create value.
Then we'd say calibrate the scope of your effort, according to some of the hard costs around data transmission and storage. Then we think as companies mature in their capabilities, and in their understanding, then you can make tweaks to your strategy, and either collect less data or collect more depending upon the value that you now have a better understanding of.