Composite Metrics

Here are some interesting examples of composite metrics - metrics whose values are determined by a mathematical formula involving other metrics. Composite metrics can be very effective in dashboards and scorecards, as they can quickly represent high-level information with a single number based on multiple underlying values (think Dow Jones Industrial Average).

The first is from traffic.com and is called the Jam Factor, which sounds like the name of a bad 80’s rock band but is an extremely useful metric.

The Traffic.com Jam Factor is like a Richter Scale for traffic. It’s an overall measure of the traffic intensity on a roadway, or on a section of a roadway. Because the Jam Factor calculation uses real-time and historical speed data from our digital sensors and those of our partners, as well as our detailed accident, construction and congestion information, it’s a comprehensive measuring tool that is unique to Traffic.com.

The Jam Factor is measured on a scale of 0-10, with 10 representing the worst traffic conditions. This numerical scale also provides color coding to give you a quick, at-a-glance picture of conditions on the roadways.

The second is a software analysis tool called WKO+ from TrainingPeaks. WKO+ provides a variety of tools that cyclists can use to monitor data from heart-rate monitors, power meters, and GPS devices to analyze their training. Working with exercise physiologists, TrainingPeaks developed two metrics that are used in their product: Training Stress Score (TSS) and Intensity Factor (IF). TSS tells you how much stress you put on your body during a workout, and IF tells you how intense the workload was compared to last months’ similar workout.

According to Gear Fisher, Chief Technology Officer at TrainingPeaks:

“The beauty of TSS and IF is that, combined, they can tell the amount of physiological stress put on a person’s body. They are all based on an individual rider’s threshold. So unlike heart-rate or even power zones, where 400 watts is 400 watts but if I weight 300 pounds and the guy next to me weighs 150 pounds the end result is something dramatically different in terms of velocity. If I go out and do 200 TSS points, or Lance Armstrong goes out and does 200 TSS points, the relative effect on each of our bodies is the same. So he put his body through the same amount of stress as I did, even though it only took me 2 hours to get 200 TSS points and it might take Lance Armstrong 3 hours – or even an hour, depending on how hard he’s going.”

The third is from a co-worker, who’s Slapdown Index is calculated from the number of hours of sleep she had the night before, the length of her commute that morning, and the frequency of annoying email requests she gets before 10:00am. A high Slapdown Index is a leading indicator of her propensity to inflict bodily harm on those who dare approach her cube.

I’ve started using Jam Factor, TSS, and Slapdown Index to optimize my daily performance. What composite metrics have you found to be useful?

DIG countdown begins

The DIG conference begins next week. Personally, I can’t wait to be part of a three day conversation that focuses on DATA, INFORMATION, and KNOWLEDGE as key enablers to better business decision-making. For sure, the “fast company” of my concern is the one that marries solid business facts with the mobilizing energy of mass collaboration. The possibilities are quite exhilarating!

I will be the facilitator of the E2.0 (knowledge) theme of the conference. In this theme, we will be exploring the opportunity and the application of E2.0 tools to drive business value within our enterprises. We are fortunate to have E2.0 veterans, Euan Semple and R. Todd Stephens, joining us to share both their practical experiences and their seasoned insights on the business value of E2.0 tools and applications within world class corporations (ATT and BBC). Both have success stories to share but, of even more interest to me, they have the battle wounds of practical experience to really dig into the topic. Also, we will have a keynote presentation by Andrew McAfee who is recognized for coining the term E2.0! What a line up.

Noting the fact that we plan to have a Twitter event connection to post everyone’s live comments and questions, I hope that we can really have an open and honest dialog that enables each of us who attend to come away with a deeper perspective on E2.0 and an expanded network to draw upon down the road.

Here are the some of the topics that we will discuss.
1) Business value of Social Computing
2) Integration of Analytics within E2.0 – Are we doing it? What is it yielding?
3) Is E2.0 bringing us closer to our Customers?
4) What is the dependent relationship between Culture and E2.0?
5) Is there a maturity model to E2.0 adoption?
6) Can a company really ignore the onslaught of Web 2.0?
7) …and what are the success stories that we should be studying!

Our only task is to bring a good attitude into the dialog. I hope that you will come with an open and inquisitive mind – a mind that is ready to listen, to poke, and to prod. The bottom line is that this conference is all about being “part of the dialog” so let’s have some fun with it.

See you there and please introduce yourself. Safe travels if you are coming from out of state. Let the conversation flow.

See Data, Feel Data, Touch Data...for free?

Much has already been said about the growth of free alternatives to Microsoft Office - between Google, Zoho and others, the competition leads predictably to questioning the incumbent as well as continued innovation from Redmond.

Meanwhile, Google may also be seeking to make a dent in the area of data visualization. Building on last year's acquisition of Gapminder's Trendanalyzer, Google released a data visualization API, essentially a platform to create interesting displays based on structured data stored in Google Docs.

Initially, there's simply a "cool" factor at work here - "If I could get that salary list, I could post a piles-of-money gadget around the office!" But are there competitive implications? It's interesting that for as many years as it's taken for real on-line competition for Office to emerge, there could be a viable alternative in the much younger data visualization space much sooner.

There are so many questions - What are Google's long-term intentions in this space? Will it be a drag for the leading BI vendors, or will it help popularize the concept and "raise all boats"? Will Google's experience in search engines mean we can expect it to lead the way with unstructured data visualization?

Quality Data helps us go GREEN!

Yesterday was another day of coming home from work late and having to force the door open to get past all the junk mail inside. After picking up, taking into the kitchen and spending 10 minutes going through I was yet again presented with another fine example of poor data quality (i.e. the majority of organizations really don’t have a grip on their customer data let alone the ability to household).

3 copies of a news letter from the same software company (no names mentioned!), the exact same letter from a State Insurance agency for both my wife and I, and then two copies of the Crate & Barrel latest summer catalog addressed to me (how on earth I became registered on their list I’ll never know!).

I wonder what the impact to the environment would be if organizations simply got a better understanding of their customer data and improved their marketing functions alone?

So once I finished my nightly chore of “shredding” I did some quick research to see what sort of impact to the environment today junk mail has. Check out the following facts listed by New America Dream:

• More than 100 million trees’ worth of bulk mail arrive in American mail boxes each year – that’s the equivalent of deforesting the entire Rocky Mountain National Park every four months. (New American Dream calculation from Conservatree and U.S. Forest Service statistics)

• In 2005, 5.8 million tons of catalogs and other direct mailings ended up in the U.S. municipal solid waste stream – enough to fill over 450,000 garbage trucks. Parked bumper to bumper these garbage trucks would extend from Atlanta to Albuquerque. Less than 36% of this ad mail was recycled. (U.S. Environmental Protection Agency)

• The production and disposal of direct mail consumes more energy than 3 million cars. (New American Dream calculation from U.S. Department of Energy and the Paper Task Force statistics)

• Citizens and local governments spend hundreds of millions of dollars per year to collect and dispose of all the bulk mail that doesn’t get recycled. (New American Dream estimate from EPA statistics)

• California's state and local governments spend $500,000 each year collecting and disposing of AOL’s direct mail disks alone. (California State Assembly)
  

With companies trying to put on a more “Green” face you would think this would be a nice eco friendly place to start. Imagine the impact of cutting bulk/junk mail in half by just knowing who your customer is and the fact that you may have multiple that live at the same address?

Even though the challenges surrounding customer data are not new, more is being spoken in the industry around Customer Data Integration. Check out Tony Fisher’s article on TDWI for an introduction on Data Quality and the Emergence of Customer Data Integration as well as go directly to such vendor sites as DataFlux and Trillium Software for innovative solutions that work to address data quality challenges, deduplication and relationship identification.

Lastly while not being one to solicit an audience, if you do have any interest in helping the environment and stopping all that junk mail look at GreenDimes. I signed up last night… I’ll let you know how it works out!

Information and Trust

In topics like business intelligence, we typically discuss “trust” from the perspective of the data being provided. Is there “one version of the truth” that creates trust in the results? Much of the focus is around structured data, meaning transactional data that is aggregated, consolidated, cleansed with context applied. This is the focus of the first two themes of the DIG conference around structured data and information. Now move to the third theme, collaboration and Enterprise 2.0, and you quickly have a different interpretation of trust…or do you?

I came upon this topic of trust in two ways this morning. The first was during my morning commute and listening to the local sports radio station. There was some back and forth about mainstream sports media bashing blogs as a form of real media. The argument was mostly centered on credentials associated with reporters versus someone with little education (their words not mine) writing a blog post. The focus was less on trust but more on the qualifications of the writer. I then read a blog post this morning by Bill Ives on the FastForward blog called “Are Us Bloggers to be Trusted” and it got me thinking. Bill makes some excellent points and the commentary from the readers make you consider the level of trust in what I refer to as an “unstructured” data set.

So that raises the question “Can content created with Enterprise 2.0 solutions, like wikis, blogs, prediction markets and social networks, be trusted?” From my perspective, I see this question being answered from two perspectives, internally and externally.

Let me start with the external perspective. What I mean by this is someone who is not a direct “employee” of a corporation but does have a relationship. An example would be a customer or a supplier of the corporation. Can that external party “trust” what they may be reading on something like a blog, where there may be considered less control then more formal communication vehicles? This question reminds me of an article in the NY Times about Wal-mart. If you read the article you will quickly realize that the Wal-mart purchasers have established trust with consumers. Product insights and predictions on topics like the future of Blu-ray versus HD DVD create a connection between the blogger and reader. Does it happen the first time a consumer reads a post from a purchaser? Doubtful, but do you ever trust something or someone upon first interaction?

So what about the internal perspective of trust? If we start to adopt the use of enterprise 2.0 to solve business issues, can we trust the “unstructured” information being provided? Remember how I started this post, with the discussion about the lack of trust in the structured data and information of a corporation. How quickly can an organization move past these challenges and trust “data and information” from an outlet like a blog, wiki or social network? Instinct says never, but if you look deeper into how enterprise 2.0 concepts can be applied to areas like business intelligence and corporate performance management, I would argue what’s the difference? When you have a hallway conversation with a colleague or a meeting to discuss quarterly results, do you “trust” the discussion? Do you trust what someone is saying to describe results and recommendations around business strategy decisions? The answer may be not always be yes, but if you don’t, the debate continues as you provide your point of view to the discussion. So why can we not quickly considered the “unstructured” data in a blog or wiki to be trustworthy and if it isn’t or at least not agreeable, continue to push the bounds on the discussion that needs to happen?

This is one aspect (and barrier) of how Enterprise 2.0 can start to provide greater value to the organization. If you look at what we are going to be discussing at DIG, it is all about helping make better decisions. To do this organizations need to move past the inherit barriers that they have towards these concepts and focus on enabling ways to build a high performing business.

For those attending the DIG Conference next week...

If you are registered to attend DIG next week, we are going to try something unique as a way to communicate and organize during the conference. We have created a Twitter user called "talkdig". If you aren't familiar to Twitter, it is considered a micro-blogging technology that allows users to communicate quickly via the web, IM or text messaging. If you want to read more about the Twitter phenomenon, see this article in the WSJ. It lays out the good and bad associated with using Twitter.

So how are we going to use Twitter at DIG? The original idea was for the Q&A sessions with our speakers. Beyond that, you can decide how you want to use it. Looking to quickly organize some attendees to discuss analytics or data architecture? Use Twitter. How about a group to head down to the strip to take in some of the Vegas night life? Use Twitter. The point being don't let us hold you back from taking advantage of one of the new ways social technologies are changing the way we work together.

So if you are interested, you should signup now and start following! It's free and only takes a few minutes. Once setup, simply send a message to twitter with "follow talkdig" and you will be part of the group. Messages will be tracked both on the twitter site and the talkdig blog.