I drive an unusual car. I live in central London, but unusually have a garage. I've never had a speeding ticket or major accident. I'm male, in my 40s, and work as a telecoms consultant. I drive less than 6000 miles a year. I can be considered an "enthusiast".
All of these are risk factors that insurance companies number-crunch each year, before offering me their annual premium. Some companies decline to offer cover. Some companies specialise in assessing various of the risk factors above, and can price keenly. Some have "live" agents & underwriters involved while others just use an online form and a big computer. They have different tweaks and tunes, such as levels of cover and varying excess (deductible) fees if you claim. If you have an accident/claim-free year, they will probably offer you a discount next year and beyond.
And that's the insurance industry's approach to pricing. It uses something similar for home insurance, health insurance and so on. The details of what and how prices are calculated vary by country, based on culture and law (eg in Europe they're not supposed to discriminate prices based on gender despite women generally being lower risks).
Telecoms, on the other hand, prefers the subscription-based model, with published price plans and perhaps a few add-ons, as well as overage and so-called value added ("out-of-bundle") charges like roaming.
Yet at the moment, much of the telecoms world is:
a) Suffering from a decline of the services which lend themselves best to plans (calls, SMS etc)
b) Trying to work out how to price broadband, given rising usage and declining costs of infrastructure, and a messy relationship between the two.
c) Trying to work out how to balance broadband and Internet access value, perhaps with additional services such as IPTV or new "managed services" completely separate from vanilla, Neutral Internet access (as I wrote about yesterday).
Also, as my colleague & erstwhile debating partner Martin Geddes points out, certain network behaviours (and applications) are worse "citizens" than others, creating problems and congestion. "Greedy" applications can almost be thought of as denial-of-service attacks on other users, consuming excess resource and causing "stationarity" problems. Something similar is true for mobile devices with poor transcievers, or even location - if you live in a basement, you probably consume more of your "fair share" of radio resource than someone on the second floor of a building with big windows. Then there's consideration of signalling (eg on/off applications always ppinging the network) as well as traffic volumes, and so on.
So maybe the telecoms industry should take a leaf out of the insurance companies' book.
Instead of getting a monthly subscription, you get quoted an annual "broadband premium". Watch lots of YouTube over LTE? Access Facebook 74 times a day from your smartphone? Drive a knackered old phone with a lousy radio chip? Download 20MB of emails at 9am in Kings Cross Station? Then sorry, but you're a poor broadband risk, and your premium is going to be really high.
The interesting thing is that if there's enough competition at a retail level (eg with MVNOs or new forms of wholesale), there ceases to be a need for full "transparency" on pricing. Each operator collects its own set of variables, crunches it through its own algorithm, and comes up with a personalised quotation. It also analyses your real usage and "risky online behaviour" to refine its premium next year. Maybe we see the emergence of companies similar to credit-scoring that rank your broadband social/anti-social scores.
Yes, there would need to be a whole range of safeguards put in place. It wouldn't be a direct copy of the insurance business. But it would certainly be a more interesting - and perhaps fairer - way to price broadband and Internet access services. (There would probably need to be assorted regulatory changes too, I know, as well as privacy challenges).
My general view is that business models - and revenues - are driven by the OSS/BSS function in telecoms. Network innovation and network-resident policy functions there to enforce certain things, manage/optimise some others, and monitor and measure statistics - but is not at the core of business model innovation. You only need to look at the years of futile and failed attempts to use DPI and PCRFs to create so-called "application-based" plans. By all means instill more intelligence in the control-layer of the IP core to manage costs and aspects of customer experience - but that's not where the revenue side of profitability will stem from.
And from the OSS/BSS side? You've been talking about "personalisation" for years, and more recently "big data". The problem has been that personalisation hasn't really been personal ("what bolt-ons do you want to buy, based on a central core plan?"). The insurance approach would need very big data to be effective, and would by definition deliver completely personalised prices.
Now yes, I know all this is a bit of a straw-man. It would be hellishly difficult to do, especially with legacy networks and legacy charging/billing systems. But I'm really curious about whether people could actually see it working, if we started from a green-field situation.
Sidenote: this is the type of properly "out of the box" thinking you get if you employ Disruptive Analysis as a consultant or business advisor. You might not agree with all the ideas - but the point is to stimulate *real* business-model and technology innovation, not just a warmed-over iteration of the last century's ideas. Contact information AT disruptive-analysis DOT com. Don't Assume.
All of these are risk factors that insurance companies number-crunch each year, before offering me their annual premium. Some companies decline to offer cover. Some companies specialise in assessing various of the risk factors above, and can price keenly. Some have "live" agents & underwriters involved while others just use an online form and a big computer. They have different tweaks and tunes, such as levels of cover and varying excess (deductible) fees if you claim. If you have an accident/claim-free year, they will probably offer you a discount next year and beyond.
And that's the insurance industry's approach to pricing. It uses something similar for home insurance, health insurance and so on. The details of what and how prices are calculated vary by country, based on culture and law (eg in Europe they're not supposed to discriminate prices based on gender despite women generally being lower risks).
Telecoms, on the other hand, prefers the subscription-based model, with published price plans and perhaps a few add-ons, as well as overage and so-called value added ("out-of-bundle") charges like roaming.
Yet at the moment, much of the telecoms world is:
a) Suffering from a decline of the services which lend themselves best to plans (calls, SMS etc)
b) Trying to work out how to price broadband, given rising usage and declining costs of infrastructure, and a messy relationship between the two.
c) Trying to work out how to balance broadband and Internet access value, perhaps with additional services such as IPTV or new "managed services" completely separate from vanilla, Neutral Internet access (as I wrote about yesterday).
Also, as my colleague & erstwhile debating partner Martin Geddes points out, certain network behaviours (and applications) are worse "citizens" than others, creating problems and congestion. "Greedy" applications can almost be thought of as denial-of-service attacks on other users, consuming excess resource and causing "stationarity" problems. Something similar is true for mobile devices with poor transcievers, or even location - if you live in a basement, you probably consume more of your "fair share" of radio resource than someone on the second floor of a building with big windows. Then there's consideration of signalling (eg on/off applications always ppinging the network) as well as traffic volumes, and so on.
So maybe the telecoms industry should take a leaf out of the insurance companies' book.
Instead of getting a monthly subscription, you get quoted an annual "broadband premium". Watch lots of YouTube over LTE? Access Facebook 74 times a day from your smartphone? Drive a knackered old phone with a lousy radio chip? Download 20MB of emails at 9am in Kings Cross Station? Then sorry, but you're a poor broadband risk, and your premium is going to be really high.
The interesting thing is that if there's enough competition at a retail level (eg with MVNOs or new forms of wholesale), there ceases to be a need for full "transparency" on pricing. Each operator collects its own set of variables, crunches it through its own algorithm, and comes up with a personalised quotation. It also analyses your real usage and "risky online behaviour" to refine its premium next year. Maybe we see the emergence of companies similar to credit-scoring that rank your broadband social/anti-social scores.
Yes, there would need to be a whole range of safeguards put in place. It wouldn't be a direct copy of the insurance business. But it would certainly be a more interesting - and perhaps fairer - way to price broadband and Internet access services. (There would probably need to be assorted regulatory changes too, I know, as well as privacy challenges).
My general view is that business models - and revenues - are driven by the OSS/BSS function in telecoms. Network innovation and network-resident policy functions there to enforce certain things, manage/optimise some others, and monitor and measure statistics - but is not at the core of business model innovation. You only need to look at the years of futile and failed attempts to use DPI and PCRFs to create so-called "application-based" plans. By all means instill more intelligence in the control-layer of the IP core to manage costs and aspects of customer experience - but that's not where the revenue side of profitability will stem from.
And from the OSS/BSS side? You've been talking about "personalisation" for years, and more recently "big data". The problem has been that personalisation hasn't really been personal ("what bolt-ons do you want to buy, based on a central core plan?"). The insurance approach would need very big data to be effective, and would by definition deliver completely personalised prices.
Now yes, I know all this is a bit of a straw-man. It would be hellishly difficult to do, especially with legacy networks and legacy charging/billing systems. But I'm really curious about whether people could actually see it working, if we started from a green-field situation.
Sidenote: this is the type of properly "out of the box" thinking you get if you employ Disruptive Analysis as a consultant or business advisor. You might not agree with all the ideas - but the point is to stimulate *real* business-model and technology innovation, not just a warmed-over iteration of the last century's ideas. Contact information AT disruptive-analysis DOT com. Don't Assume.
4 comments:
There is a slight problem with your analysis. The insurance market offers you a multitude of providers offering prices based on your characteristics. Many of those characteristics are not controlled by you, they just are: age, sex, location. And though there are some things you can control; type of car, age of car, color, distance driven, in many cases you feel less willing to. The great thing for insurance companies is however that they know the statistical relevancy of these indicators and so can hedge their bets by offering insurance to people like you. You then select based upon the offers you get, trying to judge the qualitative aspects and the financial aspects. And generally you get a fixed price offer that doesn't change with use. So though it appears personalized, it is only so to some extent.
Compare this to the telecom industry. I have never seen a telco have a good profile of users and what kind of average usage they have. For telephony we had Erlangs, but for data much less. Data communication is personal; living in a neigbourhood, being of a particular age all doesn't mean a thing for how you use the device/network.
What's more the type of offer you suggest has the propensity to end up with usage based charging. Users have hated that since time immemorial. Users prefer to pay a fixed cost. In fact many users over pay for services in months, by choosing the fixed price option. It does however save them from a bill scare in a particular month. It gives them peace of mind.
So the succesful models in this industry are based on offering consumers simple and logical price plans. These plans should be structured such that statistically they work out for the telco over time. A telco will therefore have to know what it offers, but it shouldn't bother its customers with it.
Good examples are Free/Iliad in France with their broadband offers, and mobile offers, which have followed other operators in the market to follow suit. Another one is Swisscom which has differentiated on speed alone and offers unlimited data for all. According to its investor's report, this increased data usage only by the level expected for the next quarter. So you have to bump up your scaling only one quarter and then you are up to speed.
In the insurance model a consumer can not "game" pricing. (e.g. say they don't use their car for work or don't admit a pre-existing health condition). If they do their policy is invalid.
For mobile - a consumer can just underestimate their usage to get a lower annual premium.
The worst that will happen is that they have a higher premium next year or the operator charges them for any over use.
So an operator would either lose a year's worth of revenue or be required to implement controls that would essentially make the model consumption based.
This is definitely an example of an out of the box idea. I like it! To be honest I had always considered the Telco pricing model more "advanced" than the insurance model as it has real time pricing based on actual usage whereas Insurance has a huge lag (annual) between action and increase and decrease of price. In fact with Telematics enabled usage based insurance providers are moving to a more Telco like model.
However as you point out the premium type model does have a number of advantages. Another of these is that it doesn't require any mathematics on the side of the customer. They are given a quote and they either accept it or go elsewhere. The Telcos are therefore free to make their pricing models as complex as they like.
A couple of questions to explore the idea. Annually is obviously far too long for a pricing update. How could a real time premium model work? Second how would a customer churn and still get a decent quote from a replacement operator. The incumbent operator would always have the best analysis of “risk”. Would we need portability of detailed usage records?
Also agree with the comment at 12:42. Insurance works because you the insurer has to pay out at a later date and can refuse payment. In mobile you consume the asset before you get the new premium. They would have to cut off your mobile access past certain limits. This is never popular. How to explain that to the customer without some easily understandable measure e.g. MBs?
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