I was recently talking to the CEO of a large medical device company about how IBM is gathering large scale data sets from various health sources.
With Steve Jobs spinning in his grave Apple announced a data partnership with IBM in 2015 where IBM would have access to the health meta data (everything from heart rate to sleep monitoring) collected by the Apple Watch.
In February of this year the first big data experiment was instigated;
“With ResearchKit and Watson Health Cloud, this new app will help us build the world’s largest longitudinal study to collect data on both healthy and unhealthy sleepers that can be shared with other researchers in an open-source format,”
So for the first time a precise study using significant amount of data being analysed by an AI device – IBM Watson.
So. . . I was explaining to the CEO that soon his hospital customers will be requiring his company to connect their devices to a large AI analytics cloud so that data can be amalgamated and sorted – leading to better quality treatments and pre-emptive identification of device issues. All of this is good news until the CEO realised what was going on – the vendor of the cloud hosting and analysing all of this data will require paying to use that data – so in this case the CEO’s company will be paying the cloud vendor to find out how well his devices are performing in isolation and how well they are performing against competition. . . sucking out all of the profit out of the business. . . and reducing the business to the role of “dumb pipe” manufacturer.
If, via the Internet of Things, we connect everything from the humble banana to a chain saw to a cow (a US startup has produced Fitbit for Cows, Google it) to cognitive analytics then value will move from product supplier to data analyser – probably the most significant shift in our belief in where profit lies in the history of business.
The good news about all of this is by extracting comparison data from amongst product groups – lets say chainsaws – then consumers of those product will be able to see objective product performance and reliability on a like for like basis – allowing the best products (not the best marketed products) to rise to the top. A whole new experience in making purchasing decisions.
This is just a taste of things to come – not the next decade, not in 5 years but in 2016.
This article originally appeared in the September edition of D/SRUPTION magazine – You can view the full magazine HERE