This the last one of our blog series: becoming data-driven is not just an IT responsibility. In the previous blog, we gave you some practical tips on how to write your successful DataOps implementation plan. Now, we will discuss the best practices to execute your plan and keep track of your desired outcome.
A brief recap
Without a sound DataOps implementation plan, you will risk getting off track and lost very quickly. A lousy plan will lead to spilt resources and a lack of trust from management in future data projects. Making things clear with an implementation plan helps people better understand why the change is needed, the expected outcomes, and their responsibility.
Best practices to implement your DataOps plan
Secure the resources to support the implementation.
Before starting, make sure the management gives you the necessary resources (budget, time, people), company or site-specific requirements, and responsibilities to support the implementation effort. Are these still the required ones? Are they sufficient to reach the desired outcome? If not, adapt where needed.
Communicate and promote your DataOps plan.
Make sure to involve everyone within the company when communicating about the DataOps plan. Let the leads/managers/directors that are considered as the most credible and leaders within the company promote the strategy and importance of implementing this plan. Everyone must believe the management will walk the walk.
Communicate consistently, clearly and transparently to everyone in the company:
- what is the current situation,
- what will change,
- why the change is required,
- what the desired outcome will be for all, and
- what you expect from them (their responsibilities).
Set the right expectations.
Assign goals that tap into the strengths of the people involved in the implementation. Create action points to support these set goals. Don't change everything at once. Only start with the most important action points.
Use an agile framework to facilitate collaboration and prioritise and monitor the progress of these action points. And always make sure the way of working is suitable for the company context and people involved.
Collect feedback and be approachable.
Set up a channel for people to share feedback and ideas. Don't forget to often follow-up on these. Create a safe environment to give feedback, do experiments and ask questions.
Let the people involved take ownership of their assigned goals and action points, and avoid a blaming culture. It's better to ask forgiveness for experimenting than for permission.
This best practice not only shows your gratitude and respect towards the people, but it also motivates them and helps them grow personally.
Monitor, collect feedback and adapt.
Before you start implementing, you should do an upfront measurement with the metrics and rules defined in the DataOps plan. This way, you know your starting point, goals, and you'll be able to measure your progress.
During the execution of the plan, regularly follow up on the SMART goals and action points. Evaluate the progress towards the desired outcome and consider new feedback or ideas discovered during the implementation. Are they measured correctly with the metrics and rules defined in the action plan?
Monitor if you are getting closer to the desired outcomes and outputs, and adapt where needed. Identify where improvement or refinements are needed. And most importantly, communicate results to and celebrate success with everyone in the company!
What's up next?
Implementing a DataOps plan never ends. It's an infinite loop of continuous improvements and continuous delivery/development (CI/CD). The desired outcomes will change during the process of implementation and monitoring. If you have reached this pointed, you are working truly according to the DataOps discipline. Congratulations!
Keep an eye on our future blog articles about best practices, or subscribe to our mailing list to not miss the next posts.
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