This case study deals with an engineering and construction company struggling to maintain asset master data.
AIM Consulting delivered a robotic process automation solution that saved countless hours of data entry labor while improving data quality.
Key Results:
- Built an end-to-end Robotic Process Automation (RPA) process and scripts to standardize asset data, using UIPath
- Created consistency in asset data attributes across multiple IBM Instances
- Reduced the amount of time it takes Data Entry staff to enter quality content by automating data governance
- Created a new infrastructure architecture and deployment workflow based on industry-standard best practices
Case Study Contents:
- Situation: Need for RPA Solution to Manage Asset Master Data
- Challenges: Data Entry Efforts Spread Across Groups, Instances
- Approach: Create RPA Solution, Channel Asset Data Changes
- Results: RPA Reduces Costs, Improves Data Consistency
Situation: Need for RPA Solution to Manage Asset Master Data
An engineering, procurement, and construction company specializing in government engagements manage project assets across four IBM Maximo instances. Historically, assets had been updated manually by their Client Government Service teams, located in various locations across the globe.
The challenge became maintaining asset master data. The organization continued to onboard new projects and sites, creating a backlog of asset data management, becoming a prominent issue.
As the backlog continued to snowball, stakeholders in the organization prioritized finding a sustainable solution, ultimately identifying Robotic Process Automation (RPA) as a viable path moving forward.
AIM Consulting was brought on board as a strategic partner to build a UiPath RPA and bridge the organization’s IT department and government services team gap.
Challenges: Data Entry Efforts Spread Across Groups, Instances
The manual data entry efforts had been spread across several groups and instances. While there were efforts to create a standard template, there were too many differences in each instance, and the project’s maintenance had become challenging.
These regular and varied updates presented difficulties in developing due to changing parameters.
Our consultants would need to work with stakeholders to set consistent update processes and work directly with IBM to custom-build an API that would sync with its template.
“AIM was a pleasure to work with and ultimately ensured the success of the project.
The development was a breeze, and bug resolution during testing was exceptionally fast. As a Product Owner, it’s great when you have trust in AIM to take the lead during busy times to maintain velocity.
As we build on our RPA expertise, we have to take opportunities like this to learn from experienced RPA developers. We’ve learned a lot from this experience and are very grateful for the team at AIM Consulting.”
Senior IT Manager
Approach: Create RPA Solution, Channel Asset Data Changes
Our experts came on board under the organization’s IT Team and worked directly with the business group that managed assets.
After a brief discovery phase and defining as-is business processes, we would need to ensure they utilized the team’s SCRUM approach via Microsoft Azure DevOps to plan, build, and verify code.
After a brief discovery phase, our consultants determined that the best way to create a UiPath RPA solution was to combine Microsoft Outlook, Microsoft Excel, IBM Maximo, and Oracle ODS.
This was easier said than done as we would need to overcome regular updates to the working Microsoft Excel sheet.
At the initial scope of work, the company had approximately ten attributes per asset, but the scope had increased to nearly forty attributes per asset by the end of the project. Through a series of catered communication cadences, our experts incorporated all necessary attributes into the RPA process.
From there, we set to create a mailbox to channel all asset data changes allowing the Client team to send all approved Excel Templates to a centralized place of access.
Once an update is received via the mailbox, the RPA can take over, read directly from the mailbox, process the excel template, and push changes through the IBM Maximo API in real time.
Once the RPA completes its tasks, an email is forwarded to the team to provide updates and data validation errors.
Project Timeline
Sprint 1
Reviewed requirements, defined stories, initial development
Sprint 2
Re-prioritized stories, developed custom IBM Maximo API, stood up new environments
Sprint 3
Developed metrics database, planned UAT
Sprint 4
Executed UAT, deployed to production, developed technical documentation
Results: RPA Reduces Costs, Improves Data Consistency
The organization now has a flexible UiPath RPA process that allows the organization to funnel all asset data changes, across various IBM Maximo instances, through one process.
What previously took multiple resources to manually input important asset data into an asset data management system is now handled via the RPA at rapid speeds, allowing the team to reduce licensing costs and improve data consistency.
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