This is my 151st post on this blog and time for me to stand down. I’ve enjoyed the opportunity to share some thoughts with the BCS community for over nine years. I want to take this opportunity to reflect on some of the constant challenges I’ve seen in presentations, books, articles and business cases over the last 30 years.

As the technologies develop, our ability to see the future is often limited, but what I have observed are a series of repeating errors which I think hamper our ability to explain to ourselves and wider stakeholders what is possible and the benefits of technology developments. Here goes:

  1. The next big thing: Every branch of IT hardware, software and networks seems to need some next big thing every two years which will reach market critical penetration in two to five years. Remember Google Glass? I remember a prediction only two or three years ago that by 2019 VR outside games would be larger than inside games. My experience is that businesses and the consumer cannot absorb change at the rate expected by the supply side. On a previous post I gave the example of virtual commerce in Second Life, which was going to be enormous by now.
  2. The killer app: Closely related to the above is the need for the killer app. I think that they are much rarer than advocates claim. The spreadsheet was for the PC, the browser for the WWW and desktop publishing for the MAC are clear examples of justifying the label. Going back WAP was the killer app for the mobile web. REALLY?
  3. Uniqueness: I’ve lost count of the number of ‘this is unique, so everyone will want it’ arguments I’ve sat through or read. Uniqueness is a feature (if true) and not a benefit. If you can’t explain what the user gains from the unique offering you’ve got a problem. A simple test: if Y is claimed to be unique, Google Y and count number of examples. I’ve done that for an organisation and they were surprised to find 60 pages of examples. They’d worked for over 12 months and hadn’t thought of that simple test.
  4. Integration: A belief that technical integration is a benefit without considering the other costs and barriers. A very early time I came across this was a package that integrated sales and marketing. When I sat down with a customer looking at a solution of £X cost, the cost of restructuring, culture change, retraining let alone the organisational politics was at least 10X. What was supposed to pay back in two years didn’t look like paying back ever. I remember one of the attempts to integrate across the construction supply chain that failed as the standards for the different professions were ignored by the software.
  5. Timing: Despite the Gartner hype-curve, I still see and receive ideas that are interesting as ideas, but have unrealistic expectations of timescales to revenue. One of my favourite examples was a mobile cash example that would go from proof of concept to revenue in 18 months. Sadly, I thought the core idea was one of the best I’d seen at the time, but I thought it would take 10 years or more in reality. Blockchain is the best example today of unrealistic time expectations. I suspect autonomous vehicles may run it a close second.
  6. Skills: This is one of the biggest repeating errors. If we made a breakthrough in remote robotic surgery, how long do you think it would take to scale this to widespread adoption across the health system? I recently caught up with an old contact. We’d worked together on rural IT use for remote consultations with GPs and specialists 20 YEARS AGO. Building the professional protocols, developing curricula, training the trainers and creating a critical mass of skills takes much longer than many people think.
  7. Infrastructure: After the spectrum allocation for 3G, I was involved in a series of workshops about the time to recover the investment with several stakeholders. There was much anxiety that returns had been promised faster than the roll out time for the infrastructure. I think six and seven are serious problems for the IoT. Living in an area with patchy 4G, I follow claims over 5G with some scepticism. Will I get 5G reliably before I get functioning 4G?
  8. Data standards: The deployment of barcodes was around 20 years after the technology was demonstrated. One of the key barriers was agreeing the item codes across the myriad of players in the space. As the data is becoming a bigger part of the solution, we need to innovate in this space, but it’s hard unless there is a dominant player or effective working collaborations. The battle between TCP/IP and the ISO 7-layer model is a good historical example. All over the IoT, I see this as one of the key challenges, as ownership is not always clear, especially between users, sector organisations and suppliers.
  9. Business model innovation: The key lesson of the open innovation movement, for me at least, is that many organisations fail to capitalise on their own innovations because they have a dominant business model and if they invent something which requires the model to change, the old model often wins over the new technology. In start-ups I still see the following argument in various guises; ‘We will make this go viral using the FREEMIUM model. It’s so unique 70 per cent will convert to the paid model inside six months’. This encapsulates a lot of the above examples closely packed. In an earlier post I warned that cloud deployments were likely to be deployed because of inflexibility in contractual terms. On this, I think I have been vindicated. It could have been much smoother.
  10. Misreading social change: Only a few years ago it was argued that young people were happy to share everything and didn’t care for privacy. How did that work out? In the early days expect young people to experiment and push at boundaries, but that is noise, not necessarily signal. In my experience a far more nuanced view emerges over a five - to 10-year period, as I think we are seeing now with social media. Some of the platform arguments fall in this space, especially internationally. The idea that there is a single app for transport that will work equally well in Singapore, Sao Paolo, San Francisco and Sheffield needs some evidence, not assertion.
  11. History is bunk: This famous quote permeates much of IT. Apparently, the IoT was invented in 2010 and social media in 2005. So, what exactly were people thinking of with IPv6, UPnP and TRON in the 80s and 90s as just some examples? The WELL was 1985 and there were online communities before there were modems in the late 60s.
  12. Regulation: in my experience regulation is a two-edged sword. It can enable new markets, but it can also stifle innovation. I see too many arguments that today ‘this’ is not regulated as a space so it never will be. I think it’s wise to think through what a regulatory framework might look like when it happens to avoid unnecessary rework and cost. My favourite example here was around drones. The free market apparently could sort out all the challenges and there was no need for governments to get involved. Tell that to pilots at Heathrow. 

Next time you are writing a business case or listening to one being presented, I hope that you’ll find this a helpful check list. I’ve seen some really good ideas fail to thrive because of a combination of the above. I’d like to think in 10 years’ time that this list might look very different. Make it so.

Over and out

About the author

Chris Yapp is a technology and policy futurologist. Chris has been in the IT industry since 1980. His roles have spanned Honeywell, ICL, HP, Microsoft and Capgemini. He is a Fellow of the BCS and a Fellow of the RSA.