Archive for September 2017

Yes, I meant to say prescriptive

I arrived a few minutes early to a presentation on IoT Security a few weeks ago and introduced myself to the man sitting next to me. He asked what the company I worked for did and I responded “We’re a real-time prescriptive analytics company.” He looked at me and asked “prescriptive?” I get this quite often --- most people think I’m mispronouncing predictive. Don’t get me wrong, we can do predictive analytics, but prescriptive is our specialty and the way of the future! When people correct me, I have to explain that no, I really meant to say prescriptive. This of course is followed more often than not with a blank stare as I explain the differences between predictive and prescriptive. To most people the difference in those few letters doesn’t mean much. However, in reality there is a huge difference!

Well, what’s the big deal in saying your software is predictive instead of prescriptive? Predictive analytics does just that --- it predicts. It predicts when something is going to go wrong. So for example, I’ve just created a smart refrigerator  – it can tell you’re going to run out of oranges on Tuesday, that the milk is expiring Monday and when a part is going to go out in the next 72 hours. However, that’s just it --- it predicts when these events are going to happen. It doesn’t solve anything. If it was a refrigerator that incorporated prescriptive analytics, it would not just predict these events, but solve them – hence the prescribing. So, my new refrigerator would re-order oranges and milk on Instacart and have them delivered and best of all it would fix the broken part or correct what was causing it to mal-function. So, all in all, a prescriptive solution prescribes remedies to a problem that is occurring or will occur. It doesn’t just predict when things are going to happen.

So, at the presentation, I was getting ready to launch into my speech, but I didn’t have a chance. As soon as I said “Yes, prescriptive,” the man smiled and said, “That’s what my group does too! Whenever I say it, people think I’m mispronouncing predictive.”  Maybe the prescriptive future will be here sooner than I thought!

Hidden revenue streams for smart cities

Today, many cities are toying with the idea of becoming a “smart city” or a city that actively does everything from monitoring traffic patterns to predicting when a street light will go out to analyzing any digital information its collecting. However, while these are nice to know items that can make life easier for inhabitants, lower emissions and can help reduce costs by improving efficiencies, many times these incremental savings are not enough to justify the large upfront cost of outfitting multiple items throughout a city with sensors. Not only are the upfront costs of sensors and their installation high, but also there is typically a resistance to change from city leaders who are nervous about changing their current processes and taking on the risk of implementing a “high tech” project. As a result of this, smart city managers and project owners need to be able to justify high expenses by having a measurable ROI and ensure that the city will also be able to generate ongoing revenue from these improvements rather than just decrease operating expenses.

One way to generate revenues is similar to what Kansas City (MO) has done. Kansas City installed kiosks throughout a city with maps and local information for restaurants, attractions, events and shopping. The kiosks have the potential to generate several streams of income while collecting important information. Initially, installation of the kiosks can be paid for or subsidized by a semi-permanent advertiser that can display an ad on the outside of the kiosk. Thus, there is little or no cost to the city to install the kiosks. As for the ongoing revenue, the city can sell advertising space on the screen to different advertisers who can run ads or offer coupons to users.  In addition to this, users can purchase tickets to attractions, events or public transportation from these kiosks. A small fee can be charged to the company selling the ticket. Next, the information collected from the kiosks, such as what attractions/restaurants/events are being searched for or how many people or cars are passing the kiosk can be sold to businesses in the area.  These different revenue streams should not only pay for the upkeep of these machines, but also generate extra income for a city.

Another way to generate income deals with using the information that people are voluntarily giving to governmental agencies online. Many people would rather complete forms online rather than go to a government building, pay for parking, wait in line and many times realize after they’ve done all of this that they’ve left an important piece of information at home. More and more cities are allowing inhabitants to do many tasks such as renew a license plate or city sticker online. People would probably even be willing to pay a small convenience fee to complete these services online. However, even without this convenience fee, if governments can turn the information they’re collecting online into usable data insights and not just a big dump of data, local municipalities could then generate streams of revenue selling these insights. Also, if they could determine what type of person is using their websites they could display targeted ads on their websites, which would generate another source of revenue.

Smart city initiatives can be extremely beneficial to inhabitants, local businesses and the environment, however, they can be expensive to implement. When a city is planning on starting a “smart city” project, they should try to think outside the box for revenue generating opportunities rather than just how much money will be saved through increased efficiencies. In a smart city, the possibilities are endless for saving money, improving the locals and tourists’ time in the city, minimizing environmental impact and also generating new streams of revenue.