Will Pay-Per-Use Pricing Become the Norm?

traffic jam

CIOs across the globe have embraced cloud computing for myriad reasons; however a key argument is cost savings. If a typical corporate server is utilized anywhere from 5-10% over the life of the asset, then it’s fair to argue the CIO paid ~10x too much for that asset (assuming full utilization). Thus to get better value,  a CIO then has two choices – embark on a server consolidation project—or use cloud computing models to access processing power and/or storage, when needed, on a metered basis.

Cloud computing isn’t the only place where utility based pricing is taking off. An article in the Financial Times shows how the use of “Big Data” in terms of volume, variability and velocity, is stoking a revolution in real-time, pay-per-use pricing models.

traffic jamThe FT article cites Progressive Insurance as an example. With the simple installation of a device that can measure driver speed, braking, location and other data points, Progressive can gather multiple data streams and compute a usage based pricing model for drivers that want to reduce premiums. For example, rates may vary depending on how hard a customer brakes, how “heavy they are on the accelerator”, or how many miles they drive.

The installed device works wirelessly to stream automobile data back to Progressive’s corporate headquarters, where billing computations take place in near real time.  Of course, the driver must be willing to embark upon such a pricing endeavor, and possibly lose some privacy freedoms, however this is often a small price to pay for the benefit of a pricing model that correlates safer driving habits with a lower insurance premium.

And this is just the tip of the iceberg. Going a step further to true utility based pricing, captured automobile data points also make it possible to create innovative pricing models based on other risk factors.

For example, if an insurance company decides it is riskier to drive to certain locales, or from 2am-5am, they can attach a “premium price” to those decisions, thus letting a driver choose their insurance rate.  Even more futuristic, it might be possible to be charged more or less based on discovery of how many passengers are driving with you!

Whether it is utility based pricing of electricity based on time of day, cloud computing, or even pay as you go insurance, with the explosion of “big data” and other technologies, it’s already possible to stream and collect various data, calculate a price and then bill a customer in a matter of minutes.  The key consideration will be consumer acceptance of such pricing models (considering various privacy tradeoffs) and adoption rates.

If the million “data collection” devices Progressive has installed are any indication, much less the general acceptance of utility priced cloud computing models, it appears we’ve embarked upon a journey in which it’s far too late to go back home.

Real-Time Pricing Algorithms – For or Against Us?

Christmas ball

In 2012, Cyber Monday sales climbed 30% over the previous year’s results. Indeed, Cyber Monday benefits both online retailers as they gain massive Christmas spend in one day, and consumers can shop at work or home and thus skip holiday crowds.

And yet, underneath the bustle of ringing “cyber cash registers”, a battle brews as retailers now can easily change prices, even by the second, using sophisticated algorithms to out-sell competitors. Consumers aren’t standing still though. They also have algorithmic tools available to help them determine the best prices.

Christmas ballLet’s say you are thinking about buying a big screen television from a major online retailer.  The price at 12 noon is $546.40, but you decide to go get some lunch to think about it. An hour later, you check back on that same item and now it’s priced at $547.50.  What gives?  Depending on your perspective, you’ll either end up being the beneficiary of algorithmic pricing models or the victim.

A Financial Times article notes the price of an Apple TV device sold by three major online retailers changed anywhere from 5-10% daily (both up and down) in late November. Some HDTVs changed prices by the hour.

These up to the minute changes are made possible by real time pricing algorithms that collect data from competitor websites and customer interactions on their own sites, and then make pricing adjustments based on inventory, margins, and competitive strategies.

An algorithm is really just a recipe if you will, codified into steps and executed at blinding speed by computers.  Thus, a pricing algorithm may be using inputs from competitor websites and other data sources, and then based on pre-defined logic, churn out a “price” that is then posted on a website. Typically this process is executed in seconds.

Thus, it is increasingly common –depending on the specific item, day, hour, or even minute—that prices of online items change in a moment’s notice. If keeping up with rapidly rising and falling prices seems like a shopper’s nightmare, you’re right. However, consumers also have tools to fight back.

The same FT article points out that some consumers are using websites such as Decide.com to determine the best if not the most “fair” price points. Using either Decide.com, or Decide’s convenient smartphone app, for an annual fee of $30, a consumer can access pricing predictions of items based on Decide’s predictive pricing algorithms.  Simply look up an item, and Decide.com gives its best prediction of when to buy an item and where.

Today, we take for granted that grocery store prices generally don’t change within the hour, and that prices at the gas pump (while sometimes changing intra-day) generally don’t change by the minute. As data collection processes move from overnight batch to near real time, expect more aggressive algorithmic pricing, coming to a grocer, gas pump—or theater near you!

“Pricing to Win” Makes Losers Out of Winners

Donald Tuck, Polish Prime Minister, is taking heat for the fiasco of awarding an important highway contract to a low-cost provider who couldn’t deliver. There are definitely lessons learned for every company considering the “too good to be true” contract bid.

The Financial Times posted an article titled Chinese Hit a Dead End with Road Plan in Poland.” The article cites how the Polish government embarrassingly canceled a contract given to the Chinese Overseas Engineering Group (Covec) to build a highway between Warsaw and the German border. The route is important because it will eventually shuttle traffic between Germany and Poland for the 2012 European Soccer Championships in Warsaw.

The initial bid from Covec was half the price of other bids from European firms, leading to rival charges of price dumping. In fact, competing bidders said it was impossible to build a highway for the price Covec quoted. Polish government officials signed a contract with Covec, and long story short—recently cancelled the project because the Chinese builder ran into financial difficulties when commodity prices increased. Now, the Polish government is relegated to hoping the road is at least “drivable” instead of complete by the June 2012 opening of the soccer tournament.

In the information technology space, the above story reminds me of how some aggressive vendors offer free hardware or software in order to gain entry into an account. Sometimes the special offer is a faster implementation of a complex project by “throwing in double” the consultants to finish in “half the time” of other established vendors.

To be fair, sometimes these “half price or free” deals work for companies willing to gamble. But there’s always a significant amount of risk involved. And of course there is no such thing as free software or hardware especially when maintenance contracts, managerial time, resource training and change management are involved.

So the ultimate question is; “What level of risk (strategic, financial, operational, compliance) are you comfortable accepting?” And selfishly, managers should also think about “softer considerations” such as reputation management as their good names could be attached to failed projects.

Please don’t get me wrong – sometimes “free” or reduced price contracts from vendors make sense for both the companies that offer them, and those who accept. Just make sure to properly assess risks and costs—because there will be plenty of both!

In most cases, there’s a compelling reason why a deal that seems too good to be true, really isn’t worth a second look. Polish Prime Minister Donald Tuck can certainly relate.