All information, content, documents, etc have implicit and explicit context and metadata associated with them, therefore they you might say they are structured to a certain extent.   So is there even such a thing as unstructured content?

Steve is the Chief Strategy Officer for Datanomic. Steve has more than 20 years IT experience, 14 of which have been gained specifically in data quality management. During his career, Steve has improved data quality for organizations including BT, Thomas Cook, Credit Suisse, Norwich Union and the Inland Revenue.  Steve has also held a number of senior IT roles including manager of products and services at data management specialist Kognitio and Managing Director of Tranato, a specialist data quality consultancy acquired by Datanomic in 2006.

Steve is a Charter Member of the International Association of Information and Data Quality (IAIDQ – www.iaidq.org) and Secretary of its UK Community of Practice.

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As employees today have increasingly free reign to connect and share data online, the amount of untapped organizational knowledge grows in proportion.  The very nature of online communities allow us to create personas that enable us to say whatever we want, whenever we want, and to whomever we chose.  As our virtual freedom increases, it becomes more and more difficult to identify and make use of concrete, usable information that can help the business in a tangible, measurable way. 

According to Oliver Marks, Enterprise2.0 strategist and consultant, business collaboration should be about “facilitating communication, streamlining processes and providing valuable contextual information to coworkers, against which business value can be measured as increased efficiency and awareness.”

To achieve this end, it is necessary for IM professionals and online community managers to create an environment that promotes the exchange of information with a defined and measurable objective in mind.  Much like offline collaboration, the members of the online community must be working towards a common goal and have a framework in place to start from. 

MIKE2.0 (www.openmethodology.org) has a solid, open source framework that many enterprise experts could learn from.  The community itself offers not only the traditional benefits of profile building, networking, blog posting and bookmarking, but a common goal and methodology for reaching it. 

Have you seen other online communities employing the open methodology strategy?  What advice could you give community managers to improve upon and help create business value from their community?

John Platten

John Platten is the CEO and Principal Consultant of Vivamex Limited a data quality, data migration, data warehousing and data management consultancy. John has worked in IT for over 20 years and began building data warehouses around 1995 when the concept was relatively new. 

His clients have included T-Mobile, GlaxoSmithkline, BP, and Shell where he has led data quality, data warehouse and ERP migrations into SAP projects.

While much of the discussion about information management centres on things that are new and exciting, it is easy to neglect some of the basic principles that the profession has learnt over the last decade.  Here are just five things that I think are among the most important to consider if your project is to be a success.

First, use a standard project plan.  MIKE2.0 has been available for some years now and provides a work breakdown structure which is comprehensive.  Such an approach allows you to involve contractors and multiple service providers without being locked into anyone’s proprietary method.

Second, use data models that have been published.  There are many of them around ranging from low cost publications by authors such as Len Silverston through to enterprise models provided by the major software vendors.  Even the most expensive model is typically much cheaper than the labour cost that it can save.

Third, borrow from Don Rumsfeld: “There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.”  The data warehouse is trying to manage the complexity of the entire business.  You can’t possibly know everything and hence requirements analysis should focus on the fundamental principles of the organisation and those things that are hard to undo later.

Fourth, the foundation of tomorrow’s enterprise data warehouse is unlikely to be today’s tactical solution.  Avoid the temptation to make the first iteration self-funding, the organisation has to be prepared to make an investment otherwise there are always cheaper short term solutions.

Finally, ask yourself whether your organisation is really as unique as your stakeholders think it is.  One of the most common reasons given for the use of unusual architectures or data models that don’t borrow from published materials is that the business is unique.  Everyone is looking for a point of differentiation but that doesn’t mean that you shouldn’t adopt standards where possible.  It is unlikely that the use of an unusual data warehouse architecture is going to enable a store to sell more toothpaste.  That same store, might, however, gain a real edge by combining consumer and supplier data in a new and novel way building on existing approaches to modelling the data.

Customer knowledge and experience data can provide a multitude of intelligence for companies to make better business decisions, yet it is often an untapped resource due to the complexities of data management and budget restrictions.  Yet especially in tough economic times, it is crucial to have the ability to not only listen to our customer’s needs but respond to them quickly. 

Theresa Kushner, Director of Strategic Marketing Customer Intelligence at Cisco Systems, provides a few suggestions to make the most out of your untapped customer data:

*Make use of unstructured data, such as customer inquiries
*Connect data systems such as order-entry and sales
*Help Sales, Service, Finance, and the whole company see the customer in totality
*Allow customer-facing people easy access to combined customer/company data
*Enable customers to define their profile and why they’re interested in the company
*Demonstrate to customers you can move with them as a partner

It may go without saying that many of these suggestions are easier said than done, but in your experience, have you had any success in this area?  Can you offer any advice for companies looking to capitalize on customer data, especially with a limited budget?

Peter Thomas

Peter Thomas has 20 years of experience in the IT industry; spanning business intelligence, financial systems, change management and many other areas.

Having spent the first eight years of his career as a manager in a UK software house, more recently he has developed award-winning data warehousing / business intelligence solutions that have been deployed in the European and Latin American operations of a large, multinational insurance organisation.

Peter has run several specific data quality initiatives and of course ensuring the quality of data is a major part of any successful BI project.

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