Detailed Analysis of the Legacy Data
Initially, our team analyzed the legacy work and asset management data across multiple applications. We then shared key inputs with the business and functional teams to help Evergy understand: differences in the data across multiple platforms; data inconsistencies; and data quality. This involved completing a detailed analysis of the legacy data including assets, locations, item master, work orders, requisitions, purchase orders and inventory details. The team also assessed the data from spreadsheets and stand-alone databases supporting current business functions. The team shared the detailed findings with the Generation Enterprise Asset Management business team and helped the team to develop tailored conversion approaches to bring disparate data into the planned common enterprise asset management solution.
Using the knowledge and understanding gleaned from the detailed analysis, our team also helped to develop methods and routines to cleanse a limited number of data areas. This included standardizing the data sets and merging data from additional sources to make the data set complete. Cleansed data sets were staged for the conversion routines to be processed further before loading the data into the targeted Maximo application.
Our team’s responsibility included converting supply chain data from the legacy applications to the target ERP application, set to support the supply chain functions upon deployment of the Maximo solution. Functional scope included item master, requisitions, purchase orders and inventory balances from the legacy application.
Our team worked closely with the supply chain management functional leads and ERP professionals experts to define the conversion requirements and develop a detailed mapping of everything from the target data elements to the source data structures. The team leveraged the initial detailed analysis to provide inputs to the business and functional team members to speed up the conversion mapping.
The team designed and developed the conversion routines to support the conversion and transformation rules captured in the mapping documents. Additionally, the team designed and built routines to capture conversion controls and to automate the validation checks.
Our team actively participates in mock conversions and revises the conversion routines to improve the quality of the converted data. The team continues to coordinate its conversion activities with other functional, application and conversion teams to align with the overall goals and objectives of the overall program.
Data Conversion Validation and Reconciliation
The team is helping to develop automated conversion validation routines to assist with data validation across the entire program. It is also developing automated routines to reconcile converted data across multiple target platforms. These automated reconciliations help the functional leads to confirm quality and alignment of the converted data across multiple applications. These reconciliations also bring out any conversion issues early and helps the business leads to direct remediations.
By outsourcing this project to 1898 & Co., Evergy garners numerous benefits. 1898 & Co.’s client-centric practices provided data conversion services that enhance the client’s internal flexibility and efficiency of workflow.