Enterprise DevOps: How to build a high-performing technology team

In this guest post, DevOps consultant and researcher Dr. Nicole Forsgren, PhD, tells enterprises why execution is key to building high-performing technology teams within their organisations.

I often meet with enterprise executives and leadership teams, and they all want to know what it takes to make a high-performing technology team.

They’ve read my book Accelerate: The Science of Lean Software and DevOps and my latest research in the Accelerate: State of DevOps 2018 Report (both co-authored with Jez Humble and Gene Kim), but they always ask: “If I could narrow it down to just one piece of advice to really give an organisation an edge, and help them become a high performer, what would it be?”

My first (and right) answer is that there is no one piece of advice that will apply to every organisation, since each is different, with their own unique challenges.

The key to success is to identify the things, such as technology, process or culture, currently holding the organisation back, and work to improve those until they are no longer a constraint. And then repeat the process.

This model of continuous improvement, which is actually identifying strategy, is the most effective way to accelerate an organisational or technology transformation.

However, in looking over this year’s research and checking back in with some of my leadership teams, I realised that one piece of advice would be applicable to everyone, and that is: “High performance is available to everyone, but only if they are willing to put in the work; it all comes down to execution.”

Yes, that’s right – basic execution. While revolutionary ideas and superior strategy are important and unique to your business, without the ability to execute and deliver these to market, your amazing ideas will remain trapped.

Either trapped in a slide deck or in your engineering team, without ever reaching the customer where they can truly make a difference.

If you still aren’t convinced, let’s look at some examples: cloud computing and database change management.

Cloud computing: Done right

Moving to the cloud is often an important initiative for companies today. It is also often something technical executives talk about with frustration: an important initiative that hasn’t delivered the promised value. Why is that? Lack of execution.

In the 2018 Accelerate State of DevOps Report, we asked respondents – almost 1,900 technical experts – if their products or applications were in the cloud. Later in the survey, we asked details about these products and applications they supported. Specifically, these covered five technical characteristics regarding their cloud usage:

  • On-demand self-service. Consumers can provision computing resources as needed, automatically, without any human interaction required.
  • Broad network access. Capabilities are widely available and can be accessed through heterogeneous platforms (e.g., mobile phones, tablets, laptops, and workstations).
  • Resource pooling. Provider resources are pooled in a multi-tenant model, with physical and virtual resources dynamically assigned and reassigned on-demand. The customer generally has no direct control over the exact location of provided resources, but may specify location at a higher level of abstraction (e.g., country, state, or datacentre).
  • Rapid elasticity. Capabilities can be elastically provisioned and released to rapidly scale outward or inward commensurate with demand. Consumer capabilities available for provisioning appear to be unlimited and can be appropriated in any quantity at any time.
  • Measured service. Cloud systems automatically control and optimise resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported for transparency.

The research revealed 22% of respondents (who said they were in the cloud) also said they were following all five of these essential practices. Why is this important? Because these practices are what make cloud computing, according to the National Institute of Standards and Technology’s (NIST) own definition.

And so, it follows, if teams are not executing on all five of them, they aren’t actually doing cloud. This is not necessarily the fault of the technical teams, but the leadership team, who set initiatives for the organisation and define targets.

Now, why does this matter? We found teams that met all five characteristics of cloud computing were 23 times more likely to be elite performers. This means they are able to develop and deliver software with speed, stability, and reliability — getting their ideas to their end users.

So, if you want to reap the benefits of the cloud and leverage it to really drive value to your customers, you have to execute.

Database: A hidden constraint

Database changes are often a major source of risk and delay when performing deployments so in this year’s research we also investigated the role of database change management.

Our analysis found that integrating database work into the software delivery process positively contributed to continuous delivery and a significant predictor of delivering software with speed, stability, and reliability.

Again, these are key to getting ideas and features (or even just security patches) to end users. But what do we mean by database change management? There are four key practices included in doing this right:

  • Communication. Notify upcoming database and schema changes with developers, testers, and the people that maintain your database.
  • Including teams. This goes a step beyond discussion to really including the teams involved in software delivery in discussions and designs. Involving all players is what DevOps is all about, and it will make these changes more successful.
  • Comprehensive configuration management. This means including your database changes as scripts in version control and managing them just as you do your other application code changes.
  • Visibility. Making sure everyone in the technical organisation has visibility to the progress of pending database changes is important.

To restate a point from above, when teams follow these practices, database changes don’t slow software teams down or cause problems when they perform code deployments.

These may look similar to, well, DevOps: integrating functionality throughout the pipeline and shifting left, and that’s exactly what it is.

The great news about this is we can take things we have learned about integrating and shifting left on other parts of our work (like IT operations and security) and apply them to the database.

Our analysis this year also found that database is equally important for teams at every stage of their journey, whether they were low, medium, or high performers.

We see this in our conversations in the industry: data is a hard problem and one that eventually needs to be tackled… and one that needs to be tackled with correct practices.

Particularly in data- and transaction-heavy environments, teams and organisations can leverage their data to drive value to their customers – but only when they execute on the key practices necessary.

Execution: Both simple and hard

For anyone who skips to the bottom of an article looking for the summary, here you go: execute on the basics and don’t skip steps. I acknowledge this is often difficult, but the data is definitive: teams and organisations that don’t fully execute don’t realise the benefits. The great news is this: excellence is available to everyone. Good luck!

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