Posted by ubertechmedia
How many of our daily business decisions can be attributed to the use of true quality information? Where are you getting your information from and how are you analyzing it? Ask yourself: “Am I willing to make mission-critical decisions with data that is not entirely intact to begin with?” It happens more than you would expect. The Data Warehousing Institute (TDWI) estimates that data quality problems associated with customer contact data alone cost U.S. businesses more than $600 billion per year.
John Tukey, the famous American mathematician once said: “The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data” Hard to swallow for many, but truly a profound statement. In order to achieve success in business, we must learn how to (1) wait until we have established a ‘quality database’ before making decisions from it, and (2) maximize the effectiveness of how we are visualizing and interpreting this information (uber important!).
Take for instance Procter & Gamble’s institutionalized approach to data visualization – The groundbreaking “Business Sphere” environment, and “Business Sufficiency Analytic Models.” – were both built to improve productivity and collaboration seamlessly so that P&G can focus on innovating for the consumer. In his recent Harvard Business Review article, Tom Davenport sheds additional light into the intricate steps P&G is taking to ensure decision-makers are equipped with actionable data. “P&G has placed visual displays of key information on desktops – over 50,000 P&G employees now have access to a “Decision Cockpit“, which provides decision makers with dynamic and powerful decision making tools all in one place. In addition to the desktop approach, P&G has created meeting spaces that it calls “Business Spheres” & implemented them in over 50 locations where management information is showcased for review. This strategically enables the framework for data visualization to always be kept top of mind throughout the entire organization.
The most important attribute of successful data visualization is in the simplicity of the message portrayed – in whether the decision makers “understand quickly what’s going on in the business, and decide what to do about it.” If organizational leaders are forced to spend too much time making sense of problem areas, the issues may never be resolved.
- The Art of Data Visualization: How to Tell Complex Stories Through Smart Design (openculture.com)
- The Three Elements of Successful Data Visualizations (blogs.hbr.org)
- BI Basics – Who Needs Business Intelligence (dattatreysindol.com)
- An Exploration of the Art of Data Visualization [Video] (geekosystem.com)
- Spreadsheet Reporting | Your Executive Reporting is Outdated | Domo | Blog (domo.com)
Posted by ubertechmedia
Reblogged this on UberTechMedia This move by #Twitter is intriguing– they already have promoted tweets… GigaOM reminds us all of Twitter’s organic growth potential – #hashtags being the most prized asset underlying Twitter’s entire business model.
We all kind of knew that Twitter’s path to making money was paved with data, and the announcement on Monday that it’s buying analytics startup Lucky Sort makes it official. Unless I’m totally misreading the writing on the wall, this move is all about giving advertisers — and anyone, in theory — the tools to learn about what people are talking about.
Word that Lucky Sort is shutting down and that several of its team are joining Twitter’s revenue engineering department suggests this is exactly what the acquisition aims to accomplish.
As it stands, companies use Twitter as a way to track how people are talking about them and maybe, if they’re really advanced, do some sentiment analysis. If they’re willing to pay a third party, Datasift and Gnip are more than happy to broaden marketers’ views to encompass the entirety of Twitter’s data, both real-time and historical. What…
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