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From Project to Program: Post-Implementation Review

By Sandy Kemsley

Read Time: 5 Minutes

I’ve covered a lot of business architecture topics in past posts, including vertical and end-to-end alignment, goals and incentives, different model types, process mining, and centers of excellence. In this post, I’m going to start to bring some of those themes together to look at best practices for moving from your first intelligent automation project to a successful organization-wide program.

Let’s assume that you’ve deployed your first project. If you did this right, you used “minimum viable product” principles to choose something that was big enough to be relevant, but small enough to be manageable, and you resisted scope creep along the way. It may include a broad mix of technologies, such as business process management, case management, decision management, robotic process automation, machine learning and more; or maybe you used the project to test out only one or two technologies. It may span multiple departments, or just a single team.

How do you take what you learned from this first project, whether successful or not, and leverage it in subsequent projects?

Moving from a single project to a broader program involves a few steps:
1.

Perform a post-implementation review (PIR) on your first project to figure out what worked, and what didn’t work. This is a critical step, but many organizations don’t take the time to do it, or they aren’t sure what should be in a PIR.

2.

Decide on the next project(s) that will follow the first one, which could include adding functionality or expanding the reach of the first project, or taking on a completely different business process.

3.

Gather the reusable concepts, skills and artifacts from the first project to bootstrap a center of excellence (CoE) that can be leveraged by subsequent projects.

Taken together, these steps can maximize your probability of success with an intelligent automation program, even if the first project wasn’t 100% successful.

For the remainder of this post, I’m going to focus on the first step, the post-implementation review. In my next posts, I’ll dig into how to identify good candidates for subsequent projects, and how to bootstrap a CoE from an initial project.

Post-Implementation Review (PIR)

A post-implementation review – which may begin before production deployment, but needs to include a review of the production environment — measures the success (and failure) of the project. This should be done with any significant IT project, but is especially important for your first intelligent automation project since it involves both new technologies and new ways of working. The PIR includes the following activities:

Measure the achievement of goals and KPIs that were identified at the beginning of the project.

Your intelligent automation systems should have metrics built in to assist with the measurements of those goals and KPIs. Often these are represented as return on investment (ROI) calculations: “hard” ROI such as improving productivity and reducing compliance penalties, and “soft” ROI such as improving customer satisfaction and reducing time to market. Generally, hard ROI measures are related to cutting costs and may be evident almost immediately on implementation, while soft ROI measures are related to increasing revenues and may require months before they show results.

Review the change management required to implement the project.

Change management can include departmental reorganization, for example, if an intelligent automation project centralizes a common function across several business units. Change management also includes the impact on individual team members, such as skills retraining and worker acceptance of the new methods and systems. Change management often lags behind system implementation, and can have a negative impact on the ability to meet goals.

Align this first project in the context of your end-to-end processes and organizational capabilities.

The first intelligent automation project within an organization should cover some part of a core end-to-end process, and improve one or more core capabilities.

Identify the ideas that can be reused in other projects.

Without even considering reusable code components, there can be reuse of concepts such as project methodology and solution design that can greatly assist future projects.

It’s important to take a critical look at the project during the PIR in order to understand what not only what you achieved, but what things didn’t go as well as expected. I often end up performing PIRs for my clients’ projects, and there are two main things that go wrong: the technology, and the organization.

Technology often doesn’t live up to expectations, due to vendors overhyping their products, and teams doing a bad job of designing and implementing it. That doesn’t mean that you’re going to throw it out and start over: it’s usually a matter of understanding the best practices and limitations of the technology products, and ensuring that the implementation teams understand the business requirements as well as the technology capabilities. Your PIR should identify both inappropriate usage of the technology, and mismatches between the business needs and what was built. The biggest red flag: when there is a much higher degree of customization than expected.

In almost every PIR, I also see problems caused by organizations that are unwilling to change in order to adapt to new ways of working. New technology, especially those that fall into the intelligent automation category, almost always change the way that individual tasks are done, and can cause sweeping changes to organizational structure and business models. Organizations that simply try to shoehorn new intelligent automation technology into their existing processes, organizational structure and workforce are doomed to fail. Not everything will need to be changed, but you will have to open to the idea of change in order to take the best advantage of new automation technologies. The biggest red flag: when the old way of doing things is used as the business requirements for the new project.

This should give you some ideas of what to include in a thorough post-implementation review for your first intelligent automation project. Next time, I’ll walk you through how to take what you learned in the PIR and use that to identify the best candidate for your next project.

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