Hardware compounds the challenge of businesses working to improve their data centralization #makerbusiness
The panacea of data and data science may be a little overhyped in the tech-business zeitgeist of today. The marginal utility of more and more data diminishes, but having a good centralized source, especially with vital information, is an undeniable asset. Susan Holcomb, formerly of Pebble, discussed some of the troubles at Pebble with centralizing some of the key data that they needed.
When a customer buys your product off the shelves in Best Buy, it’s hard to infer where they heard about you and to measure the impact of your marketing efforts. When a customer passively wears your product on their wrist, it’s hard to know which customers use the product every day and which ones mostly leave their watch lying in a drawer.
Data organization is a challenge for all businesses, but in fields like hardware, it’s stark how much harder it is to ascertain key information about your products and the market.
There are a few windows into ascertaining these crucial data points, but you can’t know everything. In hardware, you take what you can get.
Centralizing this data, and making sure it exists where people can understand it and access it will always be a challenge. This is true for any company, not just those in hardware. Holcomb advocates a bottom-up approach and argues that those who are using the data should be the ones to build the pathways to access it.
The top-down approach to centralizing data — the data science VP working with the marketing VP and the sales VP and the operations VP and the CEO — is too gargantuan. But doing it piecemeal — having one motivated data-worker find a collaborator in another department and moving forward on centralizing whatever little bit of data they can — might be successful.
Pebble had the right culture for that kind of bottom-up approach. We were by and large a friendly, thoughtful, generous, and independent-minded group of people. Our organizational culture emphasized a sense of autonomy, and no one was going to be offended by a junior team member taking the initiative to solve a problem they cared about. The bottom-up approach to data centralization might not work in every company, but in general I think data science managers can benefit from passing responsibility for data acquisition off to whatever members of their team are invested in said data. They’re the ones that are going to be using it — why shouldn’t they have the responsibility of advocating to get the data they need?
This may seem a little dubious, but the types and amount of data an executive might want to access doesn’t necessarily correlate to that which is extant or viable. Trusting those who use and compile the data, to build the infrastructure required to execute according to their needs, is by this very fact, attainable (if not necessarily the most holistic approach). What works in practice though, is certainly better than something that only works in one’s imagination. Or something that doesn’t work at all.
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