Technically speaking, a ‘data product’ is an insight or tool created out of existing or purposely acquired raw data that can be used to improve decision making, generally by clients, consumers or other organizations. This post discusses where they come from and where they should go to.
After 12 years spent as a Product Manager working for Enterprise Software, Startups, blue-chip retailers and financial services companies and advising many more, I have been able to boil it all down to one key skill - the ability to say 'No'. This post explains why 'No' is the one word that product managers need to be able to say with authority and comfort knowing that it will be well received (October 2011)
Walmart's interest in Jet.com led me to a 2013 Patent that might describe the e-commerce infrastructure that enables Jet to offer 'Gain Sharing'. Jet is able to take a large number of independent variables from a broad range of systems and bring them together to set a discounted price at the the cart. (August 2016)
I recently answered a post on Quora: I was tasked to build the first data analysis unit in my company, what should I do?
So I’d first be asking why. What is being expected of you and the team you will be building? Which decisions will your insights be informing? What will be done differently as a result of the analysis you provide.
Having worked on data strategy projects for some large and very large enterprises I have encountered many different business contexts for an organization to think strategically about their data. Here are some important considerations that should be made at the outset:
Opportunities in Data
Making the optimal business decision, whether at a strategic or an operational level requires information – and that information needs to be timely, accurate and at the right level. The raw data that will be used to generate that information can live in different systems, different functions and even different companies (i.e. outside the organization). Today, new insights will deliver competitive advantage – and those insights will be delivered out of data as the raw material.
There is an asymmetry between personal data held by companies and by the individual consumer. Companies know a lot about us, we don't know much at all -- even about what they know. What's the right balance and are we on our way there? (June 2013)
Omni-Channel retailing seems to be all the rage these days - aligning assortment, centralizing inventory and providing a seamless customer experience. However, there are a number of interesting startups that are innovating beyond the current Omni-channel paradigms (March 2013)
The growth of Social Media has elevated identity, privacy and big data to become vital topics for CIOs and CMOs of online businesses. Looking deeper into legislative, consumer and technology trends, I see the challenges for the post-digital organization as: Privacy, Ownership and Persistence. 'Rock, Paper, Scissors' provides a handy metaphor to describe the challenges faced by post-digital businesses. (January 2013)
Why would a retailer care about the semantic web, surely this is just another technology fad that the IT department can distract itself with instead of delivering faster transaction systems or more accurate and up-to-date reports? Not so. If fact it turns out semantic technology may enable robust solutions to your retail business users' most pressing problems. (December 2011)