To overcome the hurdles of finding, hiring and then keeping the brightest data professionals our clients continue to come up with creative ways to restructure their organization charts. Our candidates also increasingly are asking questions that go beyond the 24 month horizon of most jobs; querying, “what do I do next from this role”. In many cases these questions are becoming as common as the usual compensation questions.
It is the longer term, the most interesting candidates will require and answer to the question: “where in the Org Chart does my data role fit?”. We think the answer lies in the subtle differences between SaaS (Software as a Solution) and DaaP (Data as a Product). In the former it is the structure of the software and its ability to be generically and “horizontally” deployed that places experts in SaaS clearly in more of a services role (though for large technology companies this can be debated at more senior levels). However DaaP are better fit as a “vertical” component in any industry because of how data is created.
The rationale for this is that data, different from software, is produced in ways that are both dynamically complex and contextual. It is this “context” that directly ties data to each industries unique “work flow processes”. For example, a large asset business will collected data during production and operations that is vastly different from a company that buys product to be distributed, this differs again from a company that commerces only in “information”. Data is thus itself a “minable” product uniquely created in each company based on how work is done (workflow processes). More interestingly if we fold in a companies work flows derived from its organizational structure we can also see DaaP created from “social information” sources that can potentially be mined for value, thus adding an interesting level of complexity.
For the careers of Data Experts the implication is that career value can be created by gaining “company” and “industry” insights rather than just following high paying data roles randomly based on purely technical expertise. This “business” focus to creating longer term career value for Data Experts also has implications for data roles that are directly linked to business units within companies thus adding value to both candidates and clients. And we have recently been told by some client’s that they are creating programs to send their brightest Data Experts back for advanced degrees related to their industry (MS in various Engineering disciplines for one example) or simply sending them to get MBA’s with special focus in information management.
DaaP is thus a more interesting and potentially a more valuable way to think about how to capture the value of Mining data and translating that mining effort to the bottom line. Our view is increasingly that data mining is thus context, industry and “organization structure” specific. We see this as a platform for a reasonable mandate to possible modify a company’s organization chart to create a “desk” in the business center to manage data as a product (DaaP).
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