Is that tempting technology really useful to your business?
Unless it proves useful to your business, it was a distraction.
Recent posts have focussed on advice when using Data Science or Data Visualisation. Now it’s time we returned to focussing on commercial realities. One lesson, I learned as a senior customer insight leader, was not to get distracted by what one CEO called “hobbies“.
By that, he meant ideas, passions or technical innovations that, whilst interesting, are not relevant to what the business needs now. When coaching leaders, I still encounter businesses wasting money & time on hobby technology. So, let’s review a few recent articles focussed on business realities.
In this post, I’ll share a fascinating review of how AI is being used in today’s businesses. Plus, a summary of how insurers are using wider data sets in their digital transformation. Switching sectors, we’ll see how industrial companies are benefitting from IoT. Finally, as a salutary warning, I’ve included a damning critique. It’s a critique of IBM overhyping Watson (risking both their brand and wider perception of AI).
So, let’s begin a new month of content. We’ll focus on business applications of data, analytics, research & insight.
Is AI proving useful to your business?
As promised, let’s start with the topic of Artificial Intelligence (AI). The Harvard Business Review (HBR) recently published an excellent article. It summarises the findings of their survey. Asking 3,073 senior executives about the reality of how they were using AI.
The findings are a useful counter to over-hyped media coverage. Whilst also being an encouragement that real progress is being made. HBR found that 41% of businesses were still at the pilot stage. So, there’s still time to catch-up if you haven’t started.
A third of early adopters surveyed are able to cite revenue increases as a result, so this matters. HBR include some helpful recommendations for how to progress. I particularly liked the portfolio approach that they advocate. When advancing the use of insight in businesses, I’ve also found it helpful to diversify. By that, I mean a mix of:
- short-term profitable incremental improvements;
- longer-term riskier innovations.
HBR recommend another regular piece of advice from this blog. Don’t allow IT or Digital to lead your AI implementations in isolation. Business-led collaborations are a much surer path to achieving embedding & sustainable change.
Here is the full article. It’s well worth reading for the helpful recommendations & examples, as well as the survey results:
Is Big Data useful to your business?
Next, let’s risk moving on to the world of Insurance. As this next post acknoledges, its a sector that can be boring, especially in the minds of consumers. Raconteur Magazine published this piece. It summarises how insurers are throwing off their musty image. By embracing the need for digital transformation they are also using wider data.
Examples include advice on your driving behaviour from telematics. Plus, automatic calling of emergency services if you have a crash. More well known will be use of health trackers by Vitality to offer rewards & change behaviour.
A less well known example may be the emergence of Brolly as a digital version of an intelligent broker. Capturing more data & using machine learning, it has considerable promise.
Another reminder that progress is not advanced as vendors suggest, but still positive. The potential for insurance sector is huge. But, digital transformation projects need to consider data & insight aspects.
Here are some useful examples and a diagram of opportunities within value chains:
Is the Internet of Things (IoT) useful to your business?
But use of IoT is not limited to consumer facing businesses. Devices from smart watches to smart homes may get more press coverage, but don’t ignore manufacturing.
In another good read from Raconteur, they share how IoT is impacting product production. It may surprise you that the top 3 industries for IoT investment are manufacturing, utilities & transport. But, there are good reasons why.
From predictive maintenance, to intelligent inventory management there are many benefits. Industrial giants like GE have already demonstrated the potential of industry platforms. Now, IoT enablers manufacturers to learn more about the real use of their products.
Consumers benefit through faster fixes. Product designers can get some of the benefits of ethnographic research. Data flowing from consumers all the way back to the factories that made the device. Machine learning enabling more intelligent design refinement.
It may well be that the industrial value chain proves full value of IoT long before fancy new gadgets in the shops. Several of the points made in this article also read across sectors. So, worth reading for product innovators everywhere.
Here is the full copy, including some suggested use cases:
Is IBM Watson useful to your business?
Now, I need to be careful here. I have no direct experience of using IBM’s flagship product. So, this is not a personal review.
But, I want to include this biting critique, because it speaks to a wider malaise. On Gizmodo blog, Jennings Brown lays into the over-hyping of Watson by IBM. In my experience many technology vendors make the same mistake all the time. Whether it’s Big Data solutions, Data Science toolkits or IoT platforms.
So, in a month when we will focus on business applications, take note. If it sounds too good to be true, it (almost certainly) is. The comparison to President Trump is biting, but a great soundbite.
What is clear is that IBM needs to realise the value of transparency. I am old enough to have worked on Expert Systems and Neural Networks in the 1990s. One of the reasons that AI revolution died out was over-hype and black boxes.
Businesses need pragmatism and honesty from their suppliers. I hope the progress being made by Machine Learning libraries for R & Python help open it up. Greater understanding of techniques being used and limits of those methods would help.
Perhaps it takes such public shaming to encourage vendors like IBM to change. Stop promising to change the world, start by changing how you work with businesses.
Including plenty of ex-IBM whistleblowers, here is the full diatribe:
Is your use of technology useful to your business?
I hope this post has given you pause for thought.
Perhaps you are currently considering investment in Data Science, Big Data or IoT? If so, as a customer insight leader, I encourage you to think about your business.What are your strategic priorities? How does this investment move you forward towards those?