Electric turbines being assembled at GE's Greenville, N.C. plant
A PAIR OF REMARKABLE PROJECTS CREATED BY BEN FRY AND FATHOM MAY SEEM LIKE SIMPLE MARKETING. BUT ONE DAY SOON COULD ENTERPRISE SOFTWARE LOOK LIKE THIS?
GE has been riding the infographics train for all its worth, creating a slew of remarkable charts illustrating everything from health ailments and how their linked to how good different countries are at innovating. But they’ve rarely turned the lens onto the company’s own data, which makes these two experiments, by Ben Fry’s company Fathom, so interesting. Both look deep into the welter of data that GE’s products create everyday, and in so doing, offer a little glimpse into what could be possible when infographics make their way from Internet fad to management tool.
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The first one shows data gleaned from 713 power turbines, gathered in the course of two weeks. This data was then plugged into this nifty, navigable 3-D chart that shows how each and every turbine is performing over the course of a day:
The second shows data from 123,000 medical scans, performed on the company’s CT and MRI machines:
The charts are eye-popping, but the real star here is the data. The fact that it’s even being gathered--and the possibility that soon, it could be gathered in real time--augurs changes in the way that businesses might be run. From GE’s perspective, you can easily imagine charts like these being used to figure out whether a turbine or an MRI machine is about to break down. And if you can preempt an expensive repair, then you could potentially reduce downtime and net billions in efficiency gains. (This scenario isn’t fantasy--in fact, one GE employee recently told me that they’re working on that very idea.) In the meantime, you have companies such as Roambi, a startup backed by millions from Sequoia, which specializes in creating interactive charts that interface with a company’s databases, allowing, say, a sales manager to zoom around the performance figures of each of his sales reps.
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The point is, as the data we produce continues to grow--a trend many people call Big Data--there will be more and more value gained by simply making sense of data that already exists. Reams of raw figures like the ones hinted at above don’t help if they’re too big to be captured by human intuition. And that, ultimately, is the great hope of infographics: To help us add intelligence and insight to the digital noise buzzing around us every day.
COMMENTARY: What is data driven decision management (DDDM)? The following example should help.
In the 2003 bestseller “Moneyball,” author Michael Lewis recounts how Oakland A’s general manager Billy Beane used data-driven management to reshape a laggard major league baseball team into a world-class winner. Fast forward to the 2011 release of the movie version of Lewis’ book, and one can see how data-driven management – analytics – has come to the forefront of best practices in driving business execution. First, let’s review some of Beane’s management tenets.
Two of Beane’s methods stand out. First, instead of focusing on traditional metrics like RBIs, home runs and stolen bases, Beane discovered that winning baseball games was more strongly correlated with lesser-known statistics like on-base average, and with his hitters’ ability to refrain from wild swings at the ball under pressure. Second, he focused on elements of the game where success metrics hadn’t been developed in the past due to lack of data – for example, fielding. Beyond tracking fielding errors, a player’s performance was judged qualitatively by coaches and scouts.
So using a new playbook, Beane began to recruit players with high on-base averages, and provide consistent training and performance tracking to focus his players on getting on base and scoring runs. He also trained his organization to track new types of statistics to gain a data advantage in recruiting and player development. Then, critically, he made a full management commitment to get his entire organization aligned around the new metrics and philosophy. By 2003 the A’s were one of the winningest teams — with one of the lowest costs structures — in major league baseball.
Performance Management is an oft-heard buzzword in today’s corporate world. Its meaning varies by the industry, function and operating context, but the general concept revolves around a core notion: the systematic use of data throughout the enterprise to define and clarify goals, measure performance, increase productivity and improve results.
Performance Management rests on the premise that there are efficiency and quality gains to be captured by methodically uncovering and leveraging truths that live in existing systems, new social networking channels and current stores of data. Performance management adoption has grown rapidly in the recent environment of cost reduction, transparency, and compliance where access to data and early detection of problems and trends is mandatory. And the concept has gained popularity with the increased adoption of methods for process improvement and excellence, such as Six Sigma and Lean Manufacturing.
Performance management challenges business leaders because it elevates accountability for results to the same status as accountability for spending. This step forces significant changes in the machinery of business enterprises such as:
- Better definition of intended outcomes,i.e., more realistic, quantifiable.
- Better definition of roles and responsibilities.
- More systematic assessment and management of risks.
- Better data collection and decision-making processes, i.e., “closed loop” processes with more frequent checkpoints.
- Greater organization flexibility, i.e., more “nimble” organizations.
Data is the fuel that drives this new machinery. Data-driven performance management allows business executives to plan and manage enterprise program outcomes. Accurate and timely data creates the vital link between executive decisions and the performance of front-line workers.
Today businesesses can live or die on the basis of having too little data, too much data, the timeliness of that data in order to make prudent and timely management decision. The tremendous amount of data that exists today makes it essential that business managers develop systems and controls to manage this huge volume of data. Data no longer exists solely in our computers or servers, but it resides in the cloud, on mobile devices, on the Web in every form imaginable from forums to social networks. All forms of data need to be considered, including text, images, audio and video.
The following Knowledge Management and Data Driven Decision-Making Flow Chart explains the various steps in the management of data and how that data flows through the data funnel until sufficient knowledge is gained from that data that initiates an action or decision based on that data.
GE has taken data driven decision-management to the next level, but taking huge volumes of data and using data visualization technology, present that data in a manner that is simple to convey and understand. Data presented and analyzed in this fashion can drive quicker and better quality decision-making. GE now has the ability to determine at what capacity their electric turbines are performing by individual user, by country or continent. Likewise, the data visualizations for its MRI and scanning equiment can help it analyze how its equipment is being utilized, how often, and at what capacity. The result is the ability to make decisions about more efficient and higher capacity electric turbines and MRI and scanning equipment.
Courtesy of an article dated February 15, 2012 appearing in Fast Company Design
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