An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
They just don’t get it
Usually very few other Senior Managers / C-level Executives appreciate the value of good data. Intellectually, most usually agree with me, but when priorities are being set, data quality almost invariably gets pushed down the priority list by more 'burning' issues. Issues where managers see a more immediate impact on the bottom line.
—Steve Bennett: Leadership Lessons in Data Quality – Part 1
Identifying what’s critical
Not because I think companies need less data, but because they are going to be getting more and more data. With the emerging Web Squared environment where the World Wide Web meshes with devices, sensors, geospatial and temporal data, and the devices interact with this mesh to transform not just the consumer experience but the entire value chain. The volume of data that can be analyzed is not going to be nearly as important as the critical data to the problem you are trying to solve.
—Paul Barrett: Considering the Data Diet
Document what you do
For companies of all sizes, it still amazes me how many important processes are not documented. Some might claim they are forced into this modus operandi by expedience and/or a slimmed down the workforce; I think it's just human nature. It's hard to get people to effectively document how they do what they do.
—James MacLennan: Training and Learning: A Different POV
Be careful what you say
People share far more information about themselves – and in a much cleaner, structured form – on LinkedIn than in perhaps any other online medium... Moreover, their structured format makes it possible for LinkedIn to assemble aggregate profiles of companies, revealing composite pictures that must drive some of those companies’ legal and HR departments batty! At a higher level, LinkedIn also works well as a discovery tool – much more so now they’ve enabled faceted search. It’s still a bit tricky to explore people and companies by topic, but far more effective using LinkedIn than using any other tool I’m aware of.
—Daniel Tunkelang: Social Networking: Theory and Practice
Bringing order to business
Executives have the most to gain from a data governance program. Data governance brings order to the business, offering the ability to make effective and timely decisions. By implementing a data governance program, you can make fewer decisions based on ‘gut’ and better decisions based on knowledge. It’s an executive’s job to strive for greater control and lower risk, and that can’t be achieved without some form of data governance.
—Steve Sarsfield: 9 Questions CEO’s Should Ask About Data Governance
Continuous improvement on the data front
Users are all too accustomed to complaining about data. The goal of data quality should be continuous improvement, ensuring a process is available to fix data when it’s broken. If you want to address data quality, focus energy on the repair process. As long as your business is changing—and I hope it is—its data will continue to change. Data requirements, measurements, and the reference points for acceptability will keep changing too.
—Evan Levy: Perfect Data and Other Data Quality Myths
Less is more
Sometimes marketers believe that customers want more choice. According to an MIT Technology Review article, however, in the online dating market new research shows that, “users presented with too many choices experience cognitive overload and make poorer decisions as a result.”… “More search options (led) to less selective processing by reducing user’s cognitive resources, distracting them with irrelevant information, and reducing their ability to screen out inferior options.” In effect, users suffered from data overload where too many choices prohibited them from making an optimum decision.
—Paul Barsch: Methods to Systematically Reduce Customer Choice
A sentimental journey
Social brand sentiment is an aggregation of social data from across the real time web. From this aggregated data it is possible to gauge overall public opinion about your brand at any given time (assuming you can collect that data of course). The data source is any or all online forum where people gather and discuss their opinions from public sources like Twitter and Facebook to your own private label communities. Once collected the data can be analyzed as text and using linguistics sentiment trends can be established from the tone of the language and the type of words used to describe feelings and opinions. The more data and data sources the more likely that the sentiment represented accurately reflects online opinion trends.
—Michael Fauscette: Monitoring your brand: Sentiment analysis