Flows as well as Power BI dashboards that support this improvement initiative. In this use case, we'll see how process finding supports digital transformation.
For the company and leverage Power Platform to achieve our goals to create a resilient organization. It is one thing to create an app or an automation to improve the efficiency of a few individuals. It is a whole another thing to.
Deploy it at a company widescale. Luckily, in Power Platform, we have a very robust application lifecycle management or ALM solution that manages governance, development, deployment, and maintenance of the solution.
Created to take a project from POC to large scale deployment. Let's see how it works. So far, we've been creating our apps and flows in our sandbox environment,.
The over 1,000 supported Power Platform connectors. We even made some improvements to the app to include a chat bot which connects to the underlying data connection and is able to answer questions about the data like.
Which handle has the most case load. We have the late payment prediction flow we created in use case 2, as well as the settlement approval flow and the two SAP flows we created in use case 3,.
All of which are being tested for accuracy and issues by a select subset of users. We, of course, have our processes from process mining, including claims processing, claim settlement and settlement approval,.
Which uses task mining. In the Solution view, I can easily create a new solution and add all the objects created for our improvement initiative to that solution..
The solution will not only support simplicity in moving the solution from the testing environment to a production environment through export and import. But more importantly, it provides.
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Version control through managed solutions so that I can
Maintain different versions of the solution and potentially roll back to a previous good version if something starts breaking in the production environment,.Which is extremely important for something we will be deploying to a lot of users. Once I've added all my objects, I can see it reflected in the solution including apps, flows, and processes..
There's even a solution checker feature to ensure all the artifacts work together as intended with no conflicts. Once I've imported all my objects, I can publish and export the solution as.
Managed so it can be imported into the production environment. Once complete, I just need to download the Solution zip. Through the Power Platform Admin Center, I can easily create a production environment.
To deploy the solution. I can define the region and type of environment, add Dataverse if needed. Importantly, I can restrict access to the environment so only people in a specific security group can access it..
For this production environment, we will make it available company wide. Once my production environment is created, I can easily import my downloaded solution to this new environment..
Not only are we able to leverage ALM to deploy these improvements for company wide use, we can also visualize the performance of those improvements and even link it back to.
The overall process using process mining. Outside of the various line of business templates that process mining supports, we also support mining flows, virtual agents, as well as.
Power Apps using out-of-the-box templates as well. Let's see how this works with our settlement approval flow. In use case 3, we created an automation for the settlement approval process..
As we start rolling out
The approval and start seeing usage in the run history, we're able to visualize the history as a process. Here we see a custom report that is specifically tailored for flows where we.Show different metrics and visuals that are important to better understand run history like the number of successful or failed actions in the runs by flow version. In the Process Map, I can see.
The sequence of flow actions and the different variants based on whether or not the invoice data matched or not. I can also ask Copilot for insights and it tells me that the longest running activity is.
The RPA flow that gets data from the invoice system. As all of these process models are in Dataverse, we can easily merge the Cloud flow process with the existing claim settlement process to visualize the combined process with automation..
By leveraging the process hierarchy feature, we not only see the Cloud flow details, but also how the automation impacts the overall settlement approval process. Where the flow runs much faster and.
Switching over to our automation rate metric, we validate flow approval is now completely automated. If we look at process comparison, we can see that the approval flow results in less likelihood.
Of unwanted activities like manual approval or re-approval. With the data continually being updated, we'll be able to monitor the improvements by connecting this process to Power BI..
In use case 2, we show how easy it was to connect data from your process to your Power BI workspace to create a customized report. Now, we'll show you how you can create multiple reports,.
Connect them into a Power BI goal scorecard to actually measure progress against the goals that were set, which is a key to creating a resilient organization and.
Not just hand waving the improvements. First, we can use the same methodology used to create the compliance report for the automation report as well. We can see that all the core KPI's from.
Those improvements are in alignment with the innovation backlog, which includes approval duration, approval rework and the automation rate, which all come from our process model..
We can also add relevant metrics from the report into a scorecard through Power BI Goals, which will be shared with the rest of the leadership team and the COE team. We pick key metrics that are tied to.
The project goals so that they can all monitor the progress. We create five KPI's with relevant targets for each, including overall cycle time, cost per claim, compliance rate, automation rate,.
And on-time payment rate. These values are directly connected to the reports we created earlier and we can open up the connection for the automation rate goal and connect.
The goal to the specific value that was tracked in the report visual. Not only can we easily set up and connect these goals to data, but we can also set up alerts to notify.
The team when a Power BI goal has been reached. Using the built-in flow integration, we can easily create a flow to check the current goal versus the target, and if it exceeds the target,.
Send a tailored message in Teams chat. After some time, we receive a notification in Teams about hitting the automation rate goal of 90 percent and we can celebrate the good news..
