Category Archives: Digitalization

Smarthelp: Locating and messaging passengers

 

If you are a public transportation company: How do you tell your prospective passengers that their travel plans may have to change?

Public transportation companies know a lot about their passengers’ travel patterns, but not as much as you would think – and, surprisingly, they know less now when ticket sales have been automated than they used to know before.

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RuterBillett – a ticketing app

Let’s take a concrete company as an example: Ruter AS, the public transportation authority of Greater Oslo. Ruter is a publicly owned company that coordinates various suppliers of transportation services (bus, tram, train, some ferries) in the Oslo area. The company has been quite innovative in their use of apps, selling most of their tickets on the RuterBillett app, and having many of their customers plan their journey on the RuterReise app. The apps are very popular because they make it very easy both to figure out which bus or train to take, and to buy a ticket.

The company has a problem, though: While they know that someone bought a ticket on the ticketing app, they don’t know which particular bus, tram or other service the passenger took (a ticket typically gives you one hour of open travel on their services, no matter how many of them you use).

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RuterReise – a journey planning app

They could get some information from what people have been searching for, but the two apps are not linked, and they don’t know whether a passenger who searched for a particular route actually bought a ticket and did the journey – or not. There are many reasons for this lack of knowledge, but privacy issues – Norway has very strict laws on privacy – are import. Ruter does not want to track where its customers are travelling, at least not if it in any way involves identifying who a passenger actually is.

Not knowing where passengers are is a problem in many situations: It creates difficulties for dimensioning capacity, and it makes it difficult to communicate with passengers when something happens – such as a bus delay or cancellation.

Identifying travel patterns and communicating with passengers

The problem for Ruter is that they want to know where people are travelling (so they can figure out how many buses or trams they need to schedule), they ned to know who regularly takes certain journeys (so they know whom to send a message to if that route is not working) and they need to know who is in a certain area at a certain time (so they don’t send you a message about your bus being delayed if you are out of town, for instance). All of this is easy, except for one thing: Norway has very strict privacy laws – already quite similar to EU’s General Data Protection Regulation, which goes into effect in 2018 – and Ruter cares deeply about not being seen as a company that monitors where people travel.

In short, they need to know where you travel, but do not want to know who you are.

This is a seemingly impossible challenge, but Smarthelp Secure Infrastructure, in combination with Smart Decision Support, makes it possible. The communications platform creates an end-to-end encrypted communication channel between a central system and the smartphone. Using technology developed because we had to solve the problem of medical-level encrypted communication between emergency centers and individual users, Smarthelp has technology that allows someone to track specific information you allow access to – say, the fact that you are in a certain area, or that you regularly travel certain paths – without sharing other information, such as your name.

This would allow Ruter, when something happens, to send a message to people who a) regularly takes, say, bus route 85, and who b) is in an area where it is conceivable that they could take the bus, given their prior patterns, the time of day, and so on. For the individual passenger, this would mean that you only get pertinent messages – you don’t get messages about bus routes you don’t normally take (unless you actually get on the bus), and you don’t get messages when you are far enough from the bus that it is clear you are not going to take it anyway. In a world of information overload, this is extremely important – flood the user with many messages, and they do not read them.

The future of public transportation

A selective message and geolocation service, such as Smarthelp provides, is an evolutionary step, an optimization of the current way transportation is coordinated. In the long term (especially if we start to talk about seld-driving vehicles), the whole way we coordinate public transportation will change. As one Ruter employee told me: A public transportation company is “someone who takes you from a place you are not to a place you don’t want to go.”

The next step in public transportation is that the users tells the company not just that they want to get on the bus, but also where they want to go. I have been told that in an experiment, Telenor found that, one sunny summer afternoon, fully half of their employees (located at Fornebu outside Oslo) planned to go to Huk, a public beach on Bygdøy. The distance from Telenor’s headquarters at Fornebu is 10 minutes by car, but takes more than 30 minutes by public transportation, involving two bus routes. If Ruter had known about these travel plans, though, it could have just rolled up some buses and driven the employees directly, vastly improving the service – and avoiding clogging up the regular buses to Bygdøy.

And that is the future of public transportation: Instead of planning where you will go in terms of geography, you will tell the public transportation company where you want to go, and they will get you there. With self-driving cars, they will be able to tell you when you will be at your destination – but, perhaps, not willing to tell you the actual route. As a passenger, you probably will not care – after all, what matters to you is when you arrive, not by which route.

That would, in effect, mean that we have transitioned public transportation from line switching to packet switching, effectively turning the bus into the Internet. But that is for the future.

In the meantime, there is Smarthelp.


(I am on the board of Råd AS, a company that has developed the platform SmartHelp for Norwegian emergency services, allowing shared situational awareness, communication and privacy. The company is now seeking customers and collaborators outside this market.)

Smarthelp is a platform technology consisting of, at present, three elements: Smarthelp Rescue, an app for iPhone and Android that allows users to transmit their position to an emergency service; Smarthelp Decision Support, a decision support system which allows an operator to locate and communicate with users (both with the app and without), and Smarthelp Secure Infrastructure, a granularly encrypted communications platform for secure, private communication. If you want more information, please contact me or Fredrik Øvergård, CEO of SmartHelp.

SmartHelp: Locating employees in a crisis

If there is a crisis – do you know where your people are?

Imagine the situation: An event (terrorist attack, industrial accident, public transportation accident) of some proportion happens. Many people are hurt, lots of rumors abound, emergency services are responding. Almost immediately, the question arises: Are any of my employees affected by this – and do they need help?

At present, most organizations locate their employees by calling them or sending emails. This is slow and ineffective – when Norway was hit by a terrorist bomb in the Oslo city centre in 2011 during the summer holiday, it took one of the large newspapers more than two days of frantic telephoning to find all their employees. Most of the employees were, of course, just fine, but the company still had to locate them all. In such a situation, knowing who is not in danger quickly is very important, because it lets you concentrate resources on those who need help.

Smarthelp Decision Support, the emergency service communication platform, allows an organization to quickly – within minutes – determine where its employees are and whether they need help. Smarthelp does this while maintaining privacy of the individual employee.

Most large organizations have a system where employees register where they travel on business. For this service to work, the employee has to remember to update it, though for some companies, this happens automatically if they purchase their tickets through a specific travel agency. While this may help, people travel for pleasure, deviate from their itineraries, forget to register their travels, and purchase their tickets from the cheapest, rather than the official source. Consequently, nobody knows where they really are.

SmartHelp Decision Support (see picture) allows the company to set up a geographical area surrounding the event, and contact all their employees (based on lists of telephone numbers) to determine whether they are inside this area or not.

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Here is another example: You are responsible for security in a large company facility – say, an office building. The company receives a bomb threat which necessitates evacuating the building with thousands of employees. If the employees have SmartHelp on their phones, you can communicate with them all, and determine whether they (or at least their smartphones have left the building (limited by GPS accuracy). You can define a rallying point or area and get an automatic message as soon as someone enters the area, allowing you to quickly determine who is not accounted for. (At this point, GPS location – which we use – does not allow precise location inside a building, but that could change as WiFi locationing services get better.)

rumorsparisAnother advantage is information: In the November 2015 terrorist attack in Paris happened, there where (as is usual) lots of rumors circulating in the hundreds of thousands of Twitter messages and other social channels. With SmartHelp, the authorities would have been able to send targeted messages to specific areas, conveying a precise and autorative message across a cacophony of noise and misinformation.

SmartHelp works anywhere in the world where there is mobile reception (I have used it to signal my position to my host in Shanghai, for instance.) Privacy is handled through an ingenious cryptographic architecture that is secure and fast – the platform is certified for the medical information under the Norwegian data privacy laws, among the strictest in the world.

If you want more information, please contact me or Fredrik Øvergård, CEO of SmartHelp.


(I am on the board of Råd AS, a company that has developed the platform SmartHelp for Norwegian emergency services, allowing shared situational awareness, communication and privacy. The company is now seeking customers and collaborators outside this market.)

Smarthelp is a platform technology consisting of, at present, three elements: Smarthelp Rescue, an app for iPhone and Android that allows users to transmit their position to an emergency service; Smarthelp Decision Support, a decision support system which allows an operator to locate and communicate with users (both with the app and without), and Smarthelp Secure Infrastructure, a granularly encrypted communications platform for secure, private communication. If you want to see how the system works in a 911 central situation, see this video:

Made my day!

digøkskjermI just got the message that the new bachelor program Informatikk: Digital Økonomi og Ledelse (Informatics: Digital Economics and Management) is now the most sought-after study program in Norway, with 19 applicants per available place (514 first-priority applicants for 27 available places).

Since I have taken the initiative to this program and developed it with colleagues at the University of Oslo (where I have an adjunct position, this definitely made my day. Week, actually.

Just sayin’…

Notes from ACM Webinar on blockchain (etc.)

The Next Radical Internet Transformation: How Blockchain Technology is Transforming Business, Governments, Computing, and Security Models

Speaker: Mark Mueller-Eberstein, CEO & Founder at Adgetec Corporation, Professor at Rutgers University, Senior Research Fellow at QIIR

Moderator: Toufi Saliba, CEO, PrivacyShell and Chair of the ACM PB Conference Committee

Warning: These are notes taken live. Errors and omissions will occur. No responsibility whatsoever.

  • intro: old enough to remember the discussions in the early 90s about how the internet would change mail services – completely forgetting shopping, entertainment and others
  • Blockchain solves the problem of transferring value between Internet users without a third party
  • goes beyond the financial industry, can handle any kind of transaction
  • most of the world has access to a mobile phone, only about 20% has access to the banking system
  • Blockchain is the banking industry’s Uber movement
  • Blockchain much wider than Bitcoin, will facilitate new business models.
  • Blockchain transfers rather than copies digital assets, making sure there is only one instance of it.
    • settlement process: no clearing houses or central exchanges
    • peer-to-peer transfers, validation by network
  • Example: WeChat taking over payments in China, no link to banks
  • many commercial or government services are basically “databases” that are centrally managed, with one central point of failure
  • Blockchain allows a distributed ledger, information put in cannot be changed
    • Estonia thinking about a Blockchain in case of hacking or occupation
  • public (open), private and government blockchainsxx1
  • allows new services to existing customers, lots of inefficiencies up for grabs
    • estate records, voting, domain control, escrow, etc…
    • iPayYou allows use of Bitcoin
    • Walt Disney looking at Blockchain (DragonChain) for internal transfers, also use it for tracking supply chain to their cruise ships. Opensourced it.
  • 80% of Bitcoin mining done in China
  • regulation comes with a cost
  • Shenzhen want to be Blockchain Tech capital
  • 6-level security model, developed by William Mougayar (goes through it in detail: transaction, account, programming, distributed organizations, network (51% attacks, perhaps as low as 30%, smaller blockchains more vulnerable), governance)
  • Ethereum blockchain focusing on smart contracts: Hard forked in 2016, DAO issue where somebody hacked DAO code to siphon off money, hacking the program using the blockchain (not the blockchain),
  • credit card transaction can take up to 30 days, with disputes and everthing, Blockchain is almost instant
  • How “real” is blockchain technology
    • Goldman-Sachs invested $500m+
    • 15% of top global banks intend to roll out full-scale, commercial blockchain
    • etc.
  • what is holding it back?
    • difficult to use, understand, buy in; perception of risk and legality
    • difficult to see value for the individual
  • questions:
    • what are the incentives and adoption models?
      • different philosophies: computing power must be made available in the network: industrial mining vs. BitTorrent model, the amount of computing provided will be important, if we can find a model where just a little bit from every mobile phone is required
    • what are the hard costs of Blockchain?
      • you can google the costs. There are other approaches being developed, will post some links
    • can Blockchain be compromized by a virus?
      • theoretically, yes. Bitcoin is 10 years without, open source means verification (change is happening slowly because of code inspection)
      • comes back to incentive and governance model
  • and that was that…recording will be at webinar.acm.org in a few days.

Analytics for Strategic Management

I am starting a new executive course, Analytics for Strategic Management, with my young and very talented colleagues Alessandra Luzzi and Chandler Johnson (both with the Center for Digitization at BI Norwegian Business School).

alessandra

Alessandra Luzzi

chandler

Chandler Johnson

The course (over five modules) is aimed at managers who want to become sophisticated consumers of analytics (be it Big Data or the more regular kind). The idea is to learn just enough analytics that you know what to ask for, where the pressure points are (so you do not ask for things that cannot be done or will be prohibitively expensive). The participants will learn from cases, discussions, live examples and assignments.

Central to the course is a course analytics project, where the participants will seek out data from their own company (or, since it will be group work, someone else’s), figure out what you can do with the data, and end up, if not with a finished analysis (that might happen), at least with a well developed project specification.

The course will contain quite a bit of analytics – including a spot of Phython and R programming – again, so that the executives taking it will know what they are asking for and what is being done.

We were a bit nervous about offering this course – a technically oriented course with a February startup date. The response, however, has been excellent, with more than 20 students signed up already. In fact, wi will probably be capping the course at 30 participants, simply because it is the first time we are teaching it, and we are conscious that for the first time, 30 is more than enough, as we will be doing everything for the first time and undoubtedly change many things as we go along.

If you can’t do the course this year – here are a few stating pointers to whet your appetite:

  • Big Data is difficult to define. This is always the case with fashionable monikers – for instance, how big is “big”? – but good ol’ Wikipedia comes to the rescue, with an excellent introductory article on the concept. For me, Big Data has always been about having the entire data set instead of a sample (i.e., n = p), but I can certainly see the other dimensions of delineation suggested here.
  • Data analytics can be very profitable (PDF), but few companies manage to really mine their data for insights and actions. That’s great – more upside for those who really wants to do it!
  • Data may be big but often is bad, causing data scientists to spend most of their time fixing errors, cleaning things up and, in general, preparing for analytics rather than the analysis itself. Sometimes you can almost smell that the data is bad – I recommend The Quartz guide to bad data as a great list of indicators that something is amiss.
  • Data scientists are few, far between and expensive. There is a severe shortage of people with data analysis skills in Norway and elsewhere, and the educational systems (yours truly excepted, of course) is not responding. Good analysts are expensive. Cheap analysts – well, you get what you pay for. And, quite possibly, some analytics you may like, but not what you ought to get.
  • There is lots of data, but a shortage of models. Though you may have the data and the data scientists, that does not mean that you have good models. It is actually a problem that as soon as you have numbers – even though they are bad – they become a focal point for decision makers, who show a marked reluctance to asking where the data is coming from, what it actually means, and how the constructed models have materialised.

And with that – if you are a participant, I look forward to seeing you in February. If you are not – well, you better boogie over to BIs web pages and sign up.

Norway and self-driving cars

(This is a translation (with inevitable slight edits) from Norwegian of an op-ed Carl Störmer (who, in all fairness, had the idea) and I had in the Norwegian business newspaper Dagens Næringsliv.)

A self-driving future

Espen Andersen, BI Norwegian Business School and Carl Störmer, Jazzcode AS

Norway should become the world’s premier test laboratory for self-driving cars.

Norway needs to find new areas of development after oil – and we should go for something the whole world wants, where we have local advantages, and where we will develop deep and important knowledge even if the original idea does not succeed. We suggest that Norway should become the world’s premier test laboratory for self-driving cars – a “moon landing” we can develop far further than what we have been able to do from our expertise in sub-sea petroleum extraction.

1280px-tesla_model_s_26_x_side_by_side_at_the_gilroy_superchargerSelf-driving cars will do for personal transportation what e-mail has done for snail mail. Tesla-founder Elon Musk says Teslas will drive themselves in two hears – they already can change lanes and park themselves in your garage. The “summon“-function (a “come here”-command for your car) could, in principle, work across the entire USA.

An electrical self-driving vehicle will seldom par, choose the fastest or most economical route, always obey the traffic laws, and emit no pollutants. A society with self-driving cars can reduce the number of cars by 70-90%, free up about 30% more space in large cities, reduce traffic accidents by 90%, and drastically reduce local air pollution.

Google’s self-driving carsgoogle_self_driving_car_at_the_googleplex have driven several million kilometers without self-caused accidents, but there are still many technical problems left to solve. The cars work well in the well marked and carefully mapped roads of sunny California. The self-driving cars drive well, but the human drivers do not. But we cannot execute a sudden transition – for a long time, human and automated drivers will have to coexist.

Norway has unique advantages as a lab. In Norway, we can develop our own self-driving cars, but also be the first nation to really start using them. We do not have our own car industry to protect, we are quick to purchase and start to use new technologies, we are such a small country that decision paths are short, and should an international company make a marketing blunder in Norway, the damage will be limited to a very small market. We can easily change our laws to allow for testing of self-driving cars: Oslo, Bergen, Trondheim and Stavanger has enough traffic issues and large enough populations to suffice for a serious experiment. As a nation, we are focused on environmental issues, innovation and employment.

Norway’s bad road standard is an advantage. Norway has plenty of snow and ice, bad weather and bad roads. Today’s self-driving cars need clear road markings to be able to drive safely. But Norway has world leading capabilities in communication and coordination technology: The oil industry has learned how to continuously position ships in rough seas with an accuracy of about five centimeters. Telenor is a world-leading company in building robust mobile phone networks in complicated terrain. Technology developed for Norwegian conditions will work anywhere in the world.

Norway needs self-driving cars more than most nations. Norway is the world’s richest and most equal country, creating a modern welfare state through automation and technology-based productivity improvements. The transportation industry is over-ripe for automation. The technology can maintain productivity growth and offer a new life for many people – the blind, the old and the physically handicapped – who do not have access to cheap and simple transportation today. It will create many jobs – think before and after the smart phone here – that can be created based on abundant and cheap transportation.

Norway will win even if we don’t succeed. Lots of new technology has to be developed to make self-driving cars from experiment to production: For instance, software has to be developed that can handle extremely complicated situations when autonomous cars will have to share the road with tired human drivers. More importantly, lots of products and services can be built on top of self-driving cars, business models have to be developed, and many industries will be impacted. The insurance business, for instance, will have to adapt to a market with very few accidents. Even the donor organ market will be impacted – though traffic accident organs by no means make up the majority of organs available, there might be a shortage of available organs.

Norway has faced tremendous changes before. We have transited from being harvested ice to electric refrigertation (in the process enabling our large fishing and fish farming industries), from sail to steam shipping, from fixed line telephony to mobile phones. Our politicians have, quite wisely, created an electric car policy ensuring that we have the highest density of electric cars in the world (10% of all Teslas are sold in Norway.) Norway has everything to earn and very little to lose by going all in for self-driving cars.

Let’s do it!

Does someone have to die first?

double-classroomBlogpost for ACM Ubiquity, intro here:

Digital technology changes fast, and organizations change slowly: First using the technology as an automated, digitized version of the old way of doing things, then gradually understanding that in order to achieve productivity and functional breakthroughs. We need to leave the old metaphors behind. For this to happen, we need new mindsets, unfettered by the old way of using the technology. I wonder if my generation has the capability to do it.

Read the rest at ACM Ubiquity: Does someone have to die first?