I’m a big proponent of platform thinking. Create a platform, open it up responsibly, and enable people to create using the platform’s capabilities. It’s a way to leverage technology that’s different than in the past because it requires IT to let go of control (but not of governance) and let other people do the work.
This new attitude requires a change in the stories told, the priorities set, and the values to which an organization aspires.
It often seems like I’m pushing rope though, when I try to convince people of this future. I know a lot of resistance has to do with incentives and measures of success. For example, ROI is not always a good measure. If you’re building a platform you have to invest and it can’t be the first project to use the platform that bears the full burden on their denominator (for the math-challenged, I’m referring to the “I” in ROI).
Similarly, there can’t always be a return at the level of granularity defined by the project. In any case, I’m wandering.
I want to tell you how to think about the data in your organization.
It’s not meant to feed a silo anymore. In fact, organizations that lock their data in silos are doomed. Yes, doomed.
Benchmark to manufacturing
If you don’t read and listen to everything Horace Dediu creates, you’re missing out.
Read his latest article on Tesla’s manufacturing capacity, and what we can infer from the electric vehicle market. I’ve read it three times.
Here’s a quote, and I think it’s the most relevant part, but it’s hard to tell because the whole article is so damn good:
So why, after a few years of Model S production, is Tesla running at one fifth the speed of a BMW or Toyota plant? One obvious answer is that the company is not running 3 shifts but perhaps 2 or even 1. But why would they shut down the line when demand is infinite? If it is finite, is it really only 25k at most per quarter? That’s a paltry number considering the size of the market they operate in. BMW alone ships 2 million vehicles a year. Tesla X/S topping out at 100k a year suggests a serious limit to their opportunity.
Once the manufacturing capacity is built, it should be run to the ground (assuming demand exists) so as to maximize yield and reduce cycle time.
Data locked in silos is not “run to the ground” and you can’t possibly tell me that data is not of interest outside of the silo. I know I’m shifting verticals, but look at the way agriculture uses data… no matter how much they have, they want more.To maximize your data you’ve got to break it free from application silos; if you don’t, you’re competitor will. Click To Tweet
We need to think of data as scarce and expensive just like manufacturing capacity. Once it’s “created” it needs to be used as much as possible.
Consider Amazon’s legendary AWS genesis
Jeff Bezos said, make everything an API. And so it was. Now we have AWS a huge business in its own right.
Why wouldn’t any company create a data platform? No one has ever said “Ok, I have all the data I need” — right? In fact, we struggle moving data from spreadsheets and salesforce into powerpoint to make it look pretty. Of course, once the data is copy-pasted, it’s static and has an expiration date.
A platform would make data easily accessible. While some data is more complex to secure (like PII), much is rather straight-forward. Especially when the right governance procedures are in place.
I don’t know what would be created in every instance, but I guarantee that companies would be surprised by the innovativeness of their employees. In fact, with data available, they’d be more motivated to create interesting perspectives… perspectives that I have no doubt would be actionable.
Don’t let it happen, make it happen
Here’s the thing. Often the project (getting something running) is the final step from a team perspective, when it should be the first. A data platform wouldn’t be successful when it’s running, only when the data is being used widely.
That implies that to make a platform successful, some evangelist (at least the beginning) needs to go out and promote data availability and listen to unmet data needs to improve the platform. To break down even more silos.
I would argue, this needs to be an aggressive proactive activity. It’s not that data APIs are created to make it easy to share data… but that data sharing opportunities to improve the business have to be sought after. Because like in manufacturing, if you’re not being as efficient with your manufacturing capacity as you could be… someone else will and will win.
If you’re not using the data everywhere it might be useful, your competitor will. They’ll have an insight, or a capability that you don’t simply because they’re maximizing the utility of a resource they’ve already paid for, while you’re just letting it stay in-silo.
I’m finishing up this post as I watch some of the early panels as I prepare for my own at CA’s 2017 Government Summit, and I heard a great quote from (delightfully articulate) panelist Tarrazzia Martin a government technology expert that might help (my addition in parenthesis):Data needs to be treated like an enterprise asset (like a manufacturing plant) #API #SmartCity Click To Tweet