The cost of a Data Migration can be thought of from two angles—the Direct Cost (how much did the services cost) and the Indirect Cost ( lost revenue due to decisions based on faulty data, downtime required to correct bad data, the public relations impact of a high visibility failure, etc).
What happens when a Data Migration goes wrong? What is the impact on your project, your business and yourself?
Budget: Data issues are often addressed by throwing resources at the problem as Go Live nears. While this may keep things on schedule, it causes the budget to explode and quality to suffer.
Schedule: When Data Migration goes wrong, there is a direct impact on your project. The most obvious impact may be to the project schedule, pushing back testing events or even Go Live dates, but the true impact is more widespread. Resources expected to roll onto other projects are unable to do so as they continue to support your new schedule. Timelines for these other initiatives may also need to be adjusted to work around your dates. The domino effect continues from there, hurting not just your project but your entire organization.
Inoperable Solution: No matter how much time and effort is spent configuring and customizing your new system to meet your requirements, none of it matters if the underlying data is not right. Incorrect data may cause the system to behave in unexpected ways—or even not work at all if certain constraints are violated.
Data Loss / Corruption: Untested Data Migrations can hide all matter of problems. Data may not migrate correctly, or at all. While risk can be mitigated with thorough testing and reconciliations, the impact of lost or transposed data cannot be overstated. In addition to potential revenue loss or legal impact, for customer facing enterprises missing data can become a PR incident.
Flawed Decision Making: Reports and metrics are only as good as the data driving them. Inaccurate data leads to inaccurate forecasting and flawed decision making, which in turn impacts productivity and profitability. If inadequate attention is paid to ensuring that the data is complete, consistent, and accurate, your metrics may not be giving you a realistic picture.
Extended Downtime: Data issues identified after Go Live often need to be corrected and the corrections can cause costly downtime as they are applied. Downtime not only impacts profitability and productivity, but can also contribute to lack of trust in the new solution.
Lost Revenue: Data loss, flawed decision making and extended system downtime all contribute to lost revenue. If the system is not available to take orders or if products are not properly defined, the bottom line suffers.
Audit / Regulatory: Depending on the industry, there may be audit or regulatory statutes that dictate the depth of history that must be retained. Issues with the Data Migration may cause these requirements to be inadvertently violated.
Lack of Confidence: When the new system doesn’t act as expected or reports don’t reflect reality, they start to be seen as untrustworthy. The business will start to discount, distrust, or disregard the shiny new system and may even start agitating for a return to the old platforms or building their own workarounds.
Staff Impact: Increased hours and stress caused by struggling to keep projects on schedule impacts morale, leading to disgruntled employees and higher turnover.
Leadership Impact: When incorrect data leads to flawed decision making or causes a PR disaster, the public only sees the end result—not what led to it in the first place. This reflection leads to lack of credibility, lack of confidence and personal risk for project sponsors, decision makers and stakeholders.