Hype Cycle Management (HCM)

In the IT World HCM is typically linked to Human Capital Management, but today I want to pick up the idea of Hype Cycle. I came across a press release of Gartner Group called “Gartner’s 2013 Hype Cycle for Emerging Technologies Maps Out Evolving Relationship Between Humans and Machines” I found especially the graph very interesting on which the different technology categories are placed on the hype cycle curve. You will see for sure some of the technologies that I have been & continue to be excited about. I wonder what were the deeper analysis that have been made by Gartner in order to come to those conclusions, but this is really not the point for me writing today.

What is more the point for me today is that I have the impression that the hype cycles are getting shorter and shorter. Yet in my humble opinion real adoption cycles get much longer slower. So there seems to be a certain disconnect between the hype and the reality, which probably does not surprise anybody.

Just some examples:

Information Superhighway: This was probably one of the great starts. I remember a meeting to which I have been invited in March 2000. It was in a very prestigious office building in the very heart of Madrid. I was just joining the company and I was 29 years old. The meeting had one central presentation, which was held by John Chambers of CISCO. I have to admit that I was deeply impressed by the presentation. He stood in front of the top elite CEO’s of the Spanish Industry and made a speech about how important it is to invest for the countries future in information technology of course in networking infrastructure from his company. Yet there was a statement I believe to recall which was “If you country to continues to invest in Brick & Mortar as well as in Highways and Railroads instead of the Information Superhighway, then you will pay dearly the consequences. Not sure if it is only because of that but yes today Spain is in a deep crisis and we are missing a productive model which would help us circumvent these type of crisis. The adoption of the Information Superhighway is not doubt anymore yet we have fallen behind in Europe in regards to investing in new technologies like 4G etc. This was also the time when the 3G licenses were auctioned off at incredible prices. Yet it took about 5-6 years more in order for 3G to become a real reality.

B2B eProcurement & B2B Marketplaces: That was the hottest thing on earth back in 2000. I was amazing to see how all of a sudden none of the rules were valid anymore. Contracts were signed in record time and lawyers who normally found coma that needed to be changed had no objections. Money was just an option. Of course we all know how it ended, yet some of this has survived. The famous purchasing “reverse” auctions are still being used quite widely and also other procurement mechanism are being implemented. Yet there is no sign of those B2B Marketplaces anymore, even though it was the most promising Hype at that time.

Analytics: Has been there long before IT and just got more powerful with the tools we have today at our hands. Analytics help us to better understand the past & present in order to take better decisions for the future. Analytics is not immune to the Hype Cycle but I will get to that point shortly. Analytics is typically defined as “the discovery and communication of meaningful patterns in data” of course we must make sure that we have the right data available, that we can trust the source and thus its content.
The part of discovery in the definition is the part that makes me very curious since most of the times today the discovery of the data we use to analyze is very limited. This would be the perfect moment to throw in the next hype

BigData: This seems to really the top nudge thing right now in the market. Everybody talks about BigData and how important it is for the enterprise. Yet interesting enough the examples shown are most of the times very similar and focus back on well heard of scenarios like the social media sentiment analysis. The recommendations regarding how to start with BigData and what do with it are very diverse. I cannot somehow not picture how many large companies will implement BigData for absolutely all since it would probably simply dynamite their needs for infrastructure to host all this data (yes you can put it in the cloud but still there is a physical media on which it needs to be stored). Then there is this beautiful three-letter abbreviation I have learned to love during my studies… ROI = Return on Investment. Sorry to be nasty but I am yet to see the ROI of such massive data collection for a company.

Predictive: I learned to appreciate predictive during my statistics classed at the university. Though I have to admit that statistics was probably one of the most difficult classes I had taken. It was great to see how you could take data from the past and therefore get a good “idea” of what could be happening in the future. For a long time I did not touch this subject again until I was working in Sales Operations and I always saw a column on all decks with the name of a formula. During the sales review calls the question of “what does the formula say” was never missing. In short the formula analyzed based on the past experiences and the current input what would be the most likely landing number for the quarter. I was honestly it impressed that the formula was almost always right. Like I said almost! It was a great help in order to balance what was the human input that needed to be reported and take out the “gut feeling”. What is important is to mention that the formula required constant revision and adoption. Also the population, which was used for the measurement needed to be reviewed continuously. Augmenting or reducing the population analyzed can influence results of statistics. In short Predictive can be very powerful and will for sure take a very big part in our future lives, yet we should be careful to blindly trust.

I probably repeat myself quite a bit but I am seeing more and more companies (in this case customers) who are being more and more cautious with the hype’s. I have a certain sensation that this in turn is causing hypes to appear ever faster (an swell way to dissimulate possible failure). We will see where this ends.



About cnitschke

This blog is purely personal and reflects only my personal opinion. None of the content can be related in any way to my employer or former employers.
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