The importance of accounting for both the benefits and risks while defining the project team is critical to the project’s overall success. Implementation Partners or System Integrators often take a limited role in the data component of enterprise software implementations. While ‘data conversion’ might appear in the Statement of Work for a partner or integrator, they often narrowly define it as the ingestion of data into the new solution. This definition does not include any of the necessary, risk abating activities that support a robust data conversion strategy.

Implementation Partner’s typical data conversion activities neglect the extraction, analysis, cleansing, enrichment, harmonization, governance, transformation, and reconciliation activities that must take place. These additional activities are the most risky and difficult portion of data on an implementation and are notoriously hard to scope and estimate. These difficulties – both in scoping and execution – are the top reasons why many firms shy away from offering a complete data conversion strategy.

After considering the limited data activities included the Implementation Partner’s bid, it is critical to quantify the capabilities, risks, and benefits while planning how to resource your data team. To help calculate the impact of data to the program budget’s bottom line, the following formulas can be used:

  • Delayed Test Cycles: Weekly Project Burn Rate (not just data team burn rate) x Number of Weeks delay
  • Delayed Go Live: Weekly Project Burn Rate (not just data team burn rate) x Number of Weeks delay\
  • Overtime Required to Prevent Project Delays: +20% of data migration budget
  • Increased Conversion Load Times Caused by Pre-Validation Gaps: +10-25% of data migration of budget
  • Decreased User Acceptance Due to Data Quality Issues: +5-10% of project budget
  • Decreased Effectiveness of Solution Due to Data Quality Issues: +5-10% of project budget
  • Shared Resource Impact to Other Initiatives: +5-10% of budget of impacted initiatives
  • Increased Staff Turnover Caused by Additional Work Responsibilities: +10-15% of data migration budget

In addition to these quantitative risk factors, colleague and industry expert, Steve Novak, documented qualitative data risk factors in an insightful article at

Considering the above risk factors, finding the right resources for the team can have a big impact and open new possibilities for taking the new solution beyond its original goals. When considering the mix of internal and external people that handle the data activities, several questions should be taken into consideration:

  • What activities can only be handled by someone internal the organization? (These usually revolve around business decisions and explaining business processes)
  • What is the impact to other priorities by assigning internal resource to the project?
  • When is the last time the resource worked on similar project?
  • Are the resources familiar with data migration best practices?
  • Does the organization have right tools to help carry about the profiling, extraction, cleansing, transformation, pre-validation, etc. or will those tools need to be licensed?

To help determine the types of resources that are needed, I authored the following guide that outlines the data resources and this RACI (Responsible, Accountable, Consulted, Informed) matrix regarding data,

Benefits and Monetary Impact of the Right People, Process, and Technology

The team with the right People, Process, and Technology always opens opportunities for the project. Here are some of the quantitative benefits we’ve identified on projects that we’ve delivered over the years.

  • Risk Reduction of at least 50% across all risk factors
  • Doubled the KPI's across the 100-person project team with a targeted data team of 8-12
  • Enabled a client's data team of 30 people to focus on improving the solution with a dedicated team with 6 consultants
  • Shortened cutover time by 25%, increased data quality by 50%
  • Simultaneously reduced go-live time between phases by 50% while increasing the number of divisions per go-live from 1 to 3
  • Repeatedly saved approximately 320 hours per data area for medium to large organizations through comprehensive pre-validation processing
  • Routinely surpass implementation Partner benchmarks by +60% during the initial loads
  • While actual results and value vary from project to project, these results show the power of an effective data team.

In addition to these high-level bullet points, there is a lot more that goes into getting the resource mix right for the data team on an implementation, let’s connect and work through the questions specific to your project.

Premier is a data partner that can work with you to scope, staff, and manage data from pre-planning through post go-live data sustainment.