Are you embarking on a data migration in the near future? If so, there is one nagging question that will loom across every stage leading up to the final moment of truth as your data finally lands in the target system:

"Will the migrated data be able to support our business functions post-migration?"

Businesses often place their entire faith in a contractor or supplier. They think that because they have a contract and the supplier has a “proven method” they are protected from the failure caused by data that simply isn't ready for target system operation.

You only have to read the press and media to learn that a contract is no insurance policy.

Why does this “data readiness problem” occur?

Most businesses don’t perform large data migrations often, so project leaders and sponsors typically lack the expertise and experience to recognise the danger signs. As data migration is such a relatively immature profession, it’s all too easy to omit critical steps in the project plan that can cause poor-quality data to wreak havoc in target systems.

What should businesses be doing to ensure data readiness during data migration?

Business leaders need to take action from the outset because data migration is a business initiative. Yes, you’re migrating data, but the core activity is business transformation and for this reason it demands the necessary levels of business involvement.

Project leaders need to ensure key sponsors and experts from the business community are heavily involved in the decision-making processes for determining data readiness. They need to allocate their most valuable resources to ensure that post-migration the target systems will function like clockwork.

Even if your suppliers or contractors don't demand it, your organisation has to push for greater involvement, particularly when it comes to ensuring the readiness of data.

Why is this “business integration” tactic so uncommon?

One of the most common practices in data migration is “dumping the problem on the supplier.” This is a flawed approach driven by an assumption that data belongs to IT and can therefore be wholly outsourced to IT teams, either internally or externally.

The key fact that leaders ignore is that data is not some IT by-product that can be shunted over the fence to the contractor of choice. Data drives the business functions that fuel services and business performance. Removing business involvement from the data migration life cycle is akin to saying “we don’t care about the core functions of our business.”

This is commercial suicide and a completely outdated approach. If you want to create successful migrations, the business has to get some skin in the game.

By taking an active part in the development, testing and assurance processes of data migration, the business can guide the correct decisions and actions to ensure healthy, operational data after the data migration and beyond.

What tactics are useful for ensuring data readiness during and after data migration?

• Create contracts that stipulate business involvement during each phase of the migration

• Get the business to determine which data it will need, the rules that will bind it and the quality levels required for go-live; don’t let it use the “we need everything” response

• Perform extensive data quality assessments before, during and after the data migration

• Create use-case tests that reflect the full range of functions required of the target environment

• Perform target system testing based on full-volume data loads, not small sample sets

• Convince senior management to change its perception of data migration being an IT-centric incentive; show managers the business relevance

• At the earliest possible stage, visually demonstrate to the business how its data will look when migrated across to the target system

• Set expectations up front as to what data will be migrated across and get business leaders to sign off on these expectations

• Provide assistance to downstream data users so that they can assess their own data readiness and sign off on any changes to their data feeds

• Use modern software and methods that allow metadata, business rules and data quality management processes to create great value going forward

• Develop migration architectures and software that deliver not just one-time use, but become part of the business and IT landscape, adding value for years to come

How does your data readiness plan compare to the suggested activities above? Please add your comments below if there is anything I’ve missed or anything that needs further explanation.