(I originally wrote this April 2015 for FierceDevOps, a site which has made it either impossible or impossibly tedious to find these articles. Hence, it’s now here.)
Quick tip: if you’re in a room full managers and executives from non-technology companies and one of them asks, “what kind of company do you think we are?”…no matter what type of company they are, the answer is always “a technology company.” That’s the trope us in the technology industry have successfully deployed into the market in recent years. And, indeed, rather than this tip being backhanded mocking, it’s praise. These companies are taking advantage of the opportunity to use software and connected devices in novel ways to establish competitive advantage in their businesses. They’re angling to win customer cash by having better software and technology than their competitors.
What does it look like “on the ground,” though when it comes to “being a technology company”? I’d argue that the traditional ways we think about structuring the IT department is different than how technology companies structure themselves. To massively simplify it, traditional IT departments are oriented around working on projects, where-as technology companies are oriented around working on products.
Project oriented thinking takes in requests from an outside entity and works on solving an immediate, well understood problem. There’s often a definitive end to the project: the delivery of the new “service.” Project oriented thinking is good for creating an initial version of an application, installing and upgrading existing packaged software, setting up new offices, on-boarding employees, and other things that have a definitive completion date and well known tasks.
When organizing around this type of work, you setup a functional organization that can be assembled to implement the specific problem. Here, by “functional organization,” I mean groups of people who are defined by their expertise in something: networking, server administrator, software development, project management, audit and compliance, security, and so on. These people are typically shared across various projects as needed and usually are responsible for just what they know about. (For a very different take on how to use functional organizations, see Horace Dediu’s discussion of how Apple organizes itself.)
On-top of this, you take a request-driven approach to change management, which defines when to launch a new project or make “small” changes to an existing one (like adding a user). In the 2000s, we fancied up this concept by calling it “service management.”
Once the project is up and running, there may be something called “maintenance mode” which sees IT making sure, for example, that the ERP application has enough disk space available, that new users are added to the application, and that extra capacity is added when needed.
This mind-set is very handy when you’re dealing with keeping a bunch of products from tech vendors up and running. It’s even good if you have custom written applications that are not changed frequently. What’s also great, is that because each project is well defined at the start and has a definitive end, you can measure success and financial metrics easily: how many requests did we handle (tickets closed) this month? did we deliver on time? did we deliver on-budget? is the project profitable (thus, did we pay too much for that software or get a good deal?)
However, two things have been changing this state of affairs, pushing IT to be more exploratory in nature. As a consequence, the structure of the IT department will need to change as well to maximize ITs value to the overall business.
I often joke that it’s been impossible to see a keynote in recent years without seeing the horsemen of the digital apocalypse. These are the cliche topics that seem to come up in every keynote. Two of these lay the groundwork for why the structure of the IT department needs to change:
These two alone create a pull for more custom written software in businesses. It’s fast and cheaper to create software, and competition is relying on that to create new business models that challenge incumbents or, rather, those businesses that are not evolving how they run their business with software. Again: think of all those taxi services versus Uber.
There’s a third “horseman” in the broader industry that’s driving the need to change how IT departments are structured: the rise of SaaS. Before the advent of SaaS across application categories, software had to be run and managed in-house (or handed off to outsources to run): each company needed its own team of people to manage each instance of the application.
Source: Source: Two studies, first with 1,137 respondents, second with 1,097, involved in their company’s IT buying decisions participated in the Jan 2014 and July 2014 survey, including 470 and 445 whose company currently use public cloud. “Corporate Cloud Computing Trends,” 451 ChangeWave, Feb, 2014 & “Corporate Cloud Computing Trends,” 451 ChangeWave, Aug 2014.
As SaaS use grows more and more, that staffing need changes. How many IT staff members are needed to keep Google Apps or Microsoft’s Office 365 up and running? How many IT staff do you need to manage the storage for Salesforce or Successfactors? Indeed, I would argue that companies use more and more SaaS instead of on-premises packaged software, the staffing needs change dramatically: they lessen. You can look at this in a cost-cutting way, as in “let’s reduce the budget!” Hopefully you can look at it in a growth way instead: we’ve freed up the budget to focus on something more valuable to the business. In most cases, that thing will writing custom software. That is: developers.
This is where the shift to thinking like a product organization is vital. First of all, if you feel the need to develop more custom software — as you should! — you’ll need to hire and train more software developers, product managers, QA staff, and related folks. You’ll also want to cultivate an environment where new ideas can be explored, user-tested in production, and then quickly refined in a loop that spans mere weeks if not one week. You’ll need to become a continuous delivery and learning organization. Jonathan Murray has called this type of organization a “software factory” and has explained how he implemented the change while at Warner Music. More recently, books like Lean Enterprise have explained how this type of thinking can be applied outside of “startup culture,” whose concerns tend to be more around achieving a high valuation to get the company acquired or IPO rather than building and maintaining sustainable business models.
Setting up an organization like this requires not only developers, but creating the actual “factory” that they operate in. I think of this factory as a “platform” and the folks responsible for standing up and caring for that platform are a new type of operations staff. They’re in charge of, really, providing the “cloud” that developers effortlessly deploy and run their applications in.
This new type of IT staff has to think about how they add in as many self-service and highly elastic services in their “cloud” as possible. They too are creating a “product,” one that’s targeted at the internal developer teams and which must continually have new features added to it.
Meanwhile, your developers will be arranged into product-centric teams, hopefully working more closely with line of business managers and staff who are helping craft and grow new applications. No doubt they’ll need operations skill on the team: staff who know how to properly architect and operationalize cloud-native applications.
This is where the now classic DevOps mentality comes in: in order to properly focus on a product, the team must be responsible for all parts of that product’s life, from development through production and back. With a proper cloud platform in place and the operations team to support it, these goals are more achievable than if the product team has to start from bare metal, or work with IT through a ticket system.
To be pragmatic, you probably can’t dedicate all people fully to a product and will need to share them. This carries large risks, however, namely, making sure you properly prioritize an individual’s time and realizing that they’ll have a harder time keeping up with fewer products rather than more. Quality and ability to deliver on time will likely decrease. It may seem like an impossible goal, but often in order to stay competitive — to survive — large, seemingly impossible changes are needed