If you run a consulting practice that delivers digital transformation programmes, you already know where the risk concentrates. It is rarely the software platform. It is rarely the architecture design. It is almost always the data migration.
Gartner’s research paints a stark picture: An estimated 83% of data migration projects either fail outright or significantly exceed their budget and timeline[1]. Oracle and the Bloor Group report similar findings, with average cost overruns of around 30% and schedule slippage averaging 41%. For an IT consultancy whose reputation depends on delivery, those are not comfortable numbers.
The irony is that data migration is often treated as a secondary workstream – something that happens alongside the “real” implementation work. In practice, it is the workstream most likely to derail the entire programme.
Why data migration is harder than it looks
On paper, migration seems straightforward: Extract data from the old system, transform it to fit the new one, and load it. In reality, enterprise data environments are almost never that clean.
Most organisations have accumulated data across multiple systems over many years. Customer records may exist in three different databases with different field structures. Financial data follows one set of conventions in the UK operation and another in the European subsidiary. Product codes that were retired five years ago still appear in active records because nobody cleaned them up.
Legacy systems tend to tolerate these inconsistencies because they have evolved around them. Modern platforms – particularly cloud-based ERP systems with stricter data models – do not. What worked in the old system breaks in the new one, and the problems typically surface at the worst possible moment: After go-live, when the client expects their new platform to work flawlessly.
The Target Canada story is a well-known cautionary tale. When the retailer expanded into Canada in 2013, errors in the data migration process led to severe inventory discrepancies. Essential items were out of stock while warehouses overflowed with surplus goods. The problems contributed to the closure of all 133 stores and losses exceeding CAD $2 billion[2].
The scaling problem for consultancies
One option is to build a dedicated internal migration team. In practice, this creates its own problems.
Migration specialists need deep expertise in data profiling, cleansing, mapping, validation, and legacy system analysis. This expertise is critical during the migration phase of a programme, but demand drops sharply once that phase is complete. Maintaining a large permanent team of migration specialists creates bench cost during the gaps between projects.
Most consultancies find themselves caught between two unattractive options: Under-resourcing migration and accepting higher delivery risk, or over-investing in specialist headcount that is only fully utilised some of the time.
The partnership model
The alternative is to work with specialist data partners who focus specifically on data migration, integration, and data preparation.
This approach preserves the consultancy’s ownership of the overall transformation programme – strategy, architecture, change management, programme governance – while ensuring that the data foundation is handled by people whose entire business revolves around getting this right.
The benefits are practical rather than theoretical. A specialist partner brings proven methodologies, established tooling, and experience from repeated migration projects across multiple sectors. They have seen the failure patterns before and know how to mitigate them.
For the consultancy, this means fewer delivery surprises, tighter timelines, and a stronger client relationship. For the client, it means a data migration that has been treated as a first-class workstream rather than an afterthought.
The commercial logic
Beyond risk reduction, specialist partnerships can improve a consultancy’s economics.
Internal resources are freed to focus on the higher-margin activities that consultancies do best: Strategic advisory, solution design, and programme leadership. The data migration work is delivered at a predictable cost by a partner with clear accountability.
This also creates a differentiation story. In a competitive consulting market where most firms offer similar platform expertise, the ability to articulate a structured approach to data migration – with specialist support behind it – signals a maturity that procurement teams and CIOs recognise.
How Dajon supports consulting partners
Dajon Data Management works alongside IT consultancies and implementation partners to deliver the data components of complex transformation programmes.
Dajon’s role is focused and specific: Preparing, structuring, and migrating enterprise data so it arrives safely in the target system. Through data analysis, cleansing, mapping, and validation, Dajon ensures that the information moving between systems is ready to support operational processes from day one.
Consultancies retain full ownership of the client relationship and the programme. Dajon operates as the specialist data layer underneath, reducing the delivery risk that migration work introduces. Where legacy records need to be digitised before they can be migrated, Dajon handles that too – providing a single partner for the full data preparation chain.
For consultancies delivering ERP implementations, cloud migrations, or system consolidation programmes, the question is not whether data migration is a risk. It is how that risk is managed.
References
- Data Migration Cost Analysis & Calculator DataFlowMapper[↩]
- Failed Data Migration Projects and the Lessons Learned Hopp Tech[↩]