Tuesday, September 17, 2013

How Big Data is Disrupting the Management Consulting Industry

In a article entitled Consulting on the Cusp of Disruption, HBS professors Clay Christensen, Dina Wang, and Derek van Bever, discuss how multiple forces are disrupting the management consulting industry led by the heavyweights: McKinsey, Bain and BCG.

A chief factor at work is technology, particularly big data. Some pertinent snippets from the article on this topic:
As BTG’s CEO, Jody Miller, puts it, “Democratization and access to data are taking out a huge chunk of value and differentiation from traditional consulting firms.”
Scores of start-ups and some incumbents are also exploring the possibility of using predictive technology and big data analytics to deliver value far faster than any traditional consulting team ever could. One example is Narrative Science, which uses artificial intelligence algorithms to run analytics and extract key insights that are then delivered to clients in easy-to-read form. Similar big data firms are growing explosively, fueled by private equity and venture capital eager to jump into the high-demand, high-margin market for such productized professional services.

Only a limited number of consulting jobs can currently be productized, but that will change as consultants develop new intellectual property. New IP leads to new tool kits and frameworks, which in turn lead to further automation and technology products. We expect that as artificial intelligence and big data capabilities improve, the pace of productization will increase.
The steady invasion of hard analytics and technology (big data) is a certainty in consulting, as it has been in so many other industries. It will continue to affect the activities of consultants and the value that they add. Average costing and pricing analysis have been automated and increasingly insourced; now Salesforce.com and others are automating customer relationship analysis. What’s next? 
Consider the disruption that technology has already introduced. The big data company BeyondCore can automatically evaluate vast amounts of data, identify statistically relevant insights, and present them through an animated briefing, rendering the junior analyst role obsolete. And the marketing intelligence company Motista employs predictive models and software to deliver insights into customer emotion and motivation at a small fraction of the price of a top consulting firm. These start-ups, though they lack the brand and reputation of the incumbents, are already making inroads with Fortune 500 companies—and as partners to the incumbents. 

Saturday, September 7, 2013

Income Redistribution in the Information Economy

In her TED talk, Chrystia Freeland discusses how globalization and the technology revolution are economic drivers of income redistribution towards the top end.

Friday, September 6, 2013

Consumers Capture Economic Value Through Big Data

In a review of the book Big Data: A Revolution That Will Transform How We Live, Work, and Think, Loyd E. Eskildson summarizes the story of Farecast:
Oren Etzioni, frustrated to learn that many passengers booking a flight after he had, were able to pay less - contrary to conventional wisdom. He then 'scraped' information from a travel website from a 41-day period to forecast whether a price was a good deal or not, founding Farecast to offer this new ability. Etzioni next went on to improve the system by digesting data from a travel stie that covered most American commercial routes for a year - nearly 200 billion flight-price records. Before expanding to hotel rooms, concert tickets and used cars, Microsoft snapped up his firm ($110 million) and incorporated it into it Bing.

This is an excellent example of how big data enables consumers to capture economic value in the information economy.

Etzioni went on to co-found Decide, which in the same vein, uses big data to help consumers decide whether they should buy a product now or wait for the price to drop. A sample recommendation:

Today, it was announced that Decide was purchased by eBay for an undisclosed amount.

Monday, September 2, 2013

Will Big Data Create A Personalized Pricing Nirvana for Retailers?

In a fascinating blog post, Adam Ozimek makes the case that we will see much more individualized pricing (which economists call "first degree price discrimination") as more data mining becomes available.  

For instance, in a new working paperBen Shiller is able to use big data to massively improve his ability to predict demand for Netflix subscriptions by any given individual:

Adding the full set of variables ... including web-browsing histories and variables derived from them, substantially improves prediction – predicted probabilities range from close to zero to 91%….I find that web browsing behavior substantially raises the amount by which person-specific pricing raises variable profits.
As more and more data become available, it's easy to imagine retailers using these data to offer personalized prices for each consumer, especially for information goods where margins are large and pricing flexibility is greatest. "You want to watch Elysium tonight? Special price just for you!"  

This can substantially increase profits, and it is also likely to make products and services available at lower prices to some people who couldn't previously afford them, increasingly overall economic efficiency. At the same time, total consumers' surplus is often falls when differential pricing is introduced, as consumers with high valuations make larger payments to sellers for goods and services they would have purchased anyway.
However, that's not the end of the story.  Remember that big data can work for consumers, too.  Thanks to Google and other tools, consumers also have more and better search engines and recommendation services available.  That can intensify competition among sellers, which tends to increase consumers' surplus.
Who will come out ahead? Ultimately, it's an arms race, with those best able to use data and technology outcompeting other buyers and sellers.  In the long run, history suggests that the invisible hand tends to favor consumers as each new wave of technology is invented and diffuses.