How to start before you’re ready

Starting an Enterprise Information Management Program is a massive challenge, especially in organizations that are giving its first steps on this path.

Overcoming challenges as gathering the necessary business management sponsorship, the cost of on-premises data quality tools, the lack of the necessary skills within the organization, the absence of any measures on the costs of poor-quality data, is a long and painful process that if often abandoned before it reaches its objective.

Being prepared is overrated

Although preparation is essential, and a critical factor for the success of any initiative, it’s also common that the time and effort spent preparing overcomes the time spent doing.

Aiming at starting with a big objective, a massive data quality or and enterprise wide master data management initiative, making sure that all the conditions are perfect to start, will delay indefinitely the starting data.

Data quality is not a monolith, it as different dimensions, different techniques, applications. On the other hand, addressing data quality issues within an organization cannot be seem as a single problem. It makes it impossible to hold the focus.

Don’t get lost in getting ready, turn activities in to actions. As soon as possible. No matter how small.

• Prioritize.
• Take small steps.
• Take half steps.
• Experiment.
• Create different projects.
• Act and gather results. Is it the right approach? Is the return adequate? Where can you go from here?

The thin line between preparation and procrastination

Preparing a major initiative of this dimension is above all comfortable. It’s comfortable because nothing is taking place, there’s no commitment, no results.

Start a small initiative in a department or business unit, resolve a compliance issue that keeps generating fines, a channel that is not giving reliable information to the management, a revenue leak in the billing system.

Monitor and assess the results, implement corrective actions, modifying the practices to respond to the specific needs, making data quality part of the business process.

After this, results will turn into energy, energy into action, momentum steps in and lends a hand.