(BYOD = Bring Your Own Device. BYOB = Bring Your Own Bottle.)

January saw Obama’s inauguration, and a reflection on Bush’s analytic legacy, a discussion on whether “gut feelings” have any basis in science, a dashboard showing the best companies to work for in the US, and a quick demonstration that Malcom Gladwell was right.

February’s posts discussed the power of having the right data, and that dashboards have been around for a long, long time, but if they have poor data it’s like putting lipstick on a pig, and that it would be a crime not to include analytics in applications — but also that we’re all really bad at making decisions.

March’s posts were about BI in Bahrain, Brussels, and on the Bosphorus, making tough decisions, BI incompetency centers, scandalous bankers making more money having a shower than the rest of us make in a year, the wonderful Innovation Center and Social Network Analyzer, and more problems with bad data.

April’s posts covered more news on the Social Network Analyzer, the importance of taking account risk in business intelligence, and how BusinessObjects users think they know everything.

May included a trip to Australia with presentations on why BI projects fail and what to do about it, BI competency centers, and transforming BI; the launch of Wolfram Alpha and the inevitable problem of semantics, the launch of BusinessObjects Explorer and a not-for-profit analytics example.

June saw posts on everything you ever wanted to know about Explorer, BI market shares, Gartner and collaborative decision-making, dispenser analytics, the end of LucidEra, and the start of Recovery Act analytics.

July saw some more great examples of government BI transparency, a fun opportunity to test your decision-making skills, predictions about the end of relational databases and augmented BI reality.

August saw presentations in Belgium and South Africa, the launch of SAP’s sustainability dashboards, and a discussion of whether anybody cares about BI market share.

September’s posts included the first BI Fails and BI Briefs, including my opinions on BI futures, why it’s important to have more than one KPI, and the most annoying business words of the year.

October’s posts included how to incorporate live twitter into PowerPoint using Xcelsius, the problems of manual analysis and justice, and highlights of SAP TechEd in Vienna.

November’s posts included how to use Twitter to surf through traffic, the death of OLAP, and tracking baby’s KPIs

December saw Explorer for the iphone, the release of a new version of Xcelsius, some Season’s Greetings showing off the new features, and a great roundup of posts for the year.

Thank you for reading, and I look forward to 2010!

Enterprise social network analysis is clearly an essential part of getting a real return on investment on Web 2.0 technologies within organizations — something that has so far proved difficult.

Today, the “way organizations work” typically has little to do with the official department structures. Organizations are becoming increasingly networked and collaborative, with flat hierarchies, multiple reporting relationships, and a focus on cross-functional initiatives.

Tools like the social network analyzer can help illuminate the “real” organizational structures that are driving the business — and this is essential if we’re to deliver on the promise of translating high-level strategy into low-level execution through aligned objectives.

My company, SAP, has been undergoing extensive reorganization over the last few years — partly because it’s simply the nature of the technology business, but also because of the large BusinessObjects acquistion, and as a reaction to the recent economic downturn.

We have implemented the social network analyzer prototype within our own organization, and users have reported that it’s an extremely valuable tool for discovering links with co-workers. If you find yourself on a call with someone you haven’t yet met, you can not only look up their traditional employee profile, but also find out what other links exist between you, such as the common contacts you both work with. 

As with any new technology, getting the full benefits will require changes to way companies work. In particular, there will have to clear ownership of “network relationshp management” within organizations: ensuring that all the right people in the right teams are working together as they should.

This is perhaps a great opportunity for the human resources role to be able to really show the value of people and their interactions to the overall functioning of the company.

Enterprise social network analytics is a step towards the future of “business user applications”, and we should expect to see variants of this type of functionality embedded in almost every corporate application.

When I was growing up, my father always insisted that “business was all about relationships” (I didn’t pay much attention, sadly). But relationships can be complicated, so if you want to have a head start figuring out how your company works, download the prototype and start giving us feedback on how to make it better!

(OK, so I know puns are the lowest form of wit… apologies)

Thanks to Michael Thompson for the (real) customer quote!

All those financial wizards were making a fortune based on the money they were “creating” — money that has since turned out to be largely fictitious. Top hedge fund managers were earning more in the time it took for an average New York City cab ride (8 minutes) than the average American made in a year.

As I said with a cartoon at the time: “who’s being taken for a ride?!”

Top hedge fund managers made over $657M in 2006. You can use this handy calculator to work out how long it took them to make more than you did all year — the time to brush their teeth? Take a shower? Commute?

(model below — you will probably have to connect directly to the site to see it)

Unbelievably, the financial industry apparently STILL thinks that million-dollar bonuses are perfectly reasonable for work they do (for example, it’s argued that it’s needed to retain the “best and brightest” at AIG).

Benchmarking is a great practice — but you have to know when to update your benchmarks!

Sources: Pay statistics, time usage stats, NY cab ride, commute, TV watching. Model built using Crystal Xcelsius.