Business leaders and managers at all levels within an organisation make hundreds of important decisions throughout the year and nearly all of them are driven by data.

• Which product lines do we need to drop?
• Which workers do we need to reward?
• Which competitors do we need to outperform?
• Which divisional heads need to be replaced?

You've no doubt met the full spectrum of management professionals. Some rely on “gut instinct” and their intuition to fuel their decision-making process. Others go to the other extreme and refuse to take decisive action until they have every ounce of data available.

The decision-making process is essentially an information chain that regular readers will know is a perennial topic here on the Data Roundtable. What’s more, if you want to get support for data quality from senior management, then you can find allies by improving the quality of information that lies along these decision information chains.

Case in point: we recently switched content platforms on Data Quality Pro, but before making the switch I pored over reams of data from analytic applications, member interviews and as much data as I can muster. The decision-making process was difficult because statistics like web traffic can vary considerably between different statistical packages. So, I had to make sure that enough reference points were established. This process took time – about six months – before I was confident it was time to create a new chapter in the site's history.

The same challenges greets managers every day. Can I trust this dip in product sales data when our account managers say demand is growing? Why is this division is experiencing double-digit growth when other divisions are nose-diving?

Data quality can support this decision making process because what the manager needs is not more business intelligence apps but greater trust. When trust is variable then it’s not just the quality of the decision-making that is impaired, it’s the waste of time caused by delays that is often most damaging.

Trust comes from developing information chains that are fully governed and managed by data quality processes. There is continuous improvement, regular monitoring and comprehensive metrics that are meaningful to management. They don't need profiling stats, completeness percentages and dependency analyses. They want a verdict that maps to the decision chain. Can I make decisions along this information chain? Do I have all the information I need?

Decision making is a data quality process that requires an end-to-end view of data quality across multiple information chains, not just tables in isolation.

If you can demonstrate that your team can deliver on this requirement and help managers create faster, more accurate decision, then you’ll create an ally for life. What’s more, when new managers come in they're far less likely to shut you down because they'll be introducing risk – and that’s something all leaders are keen to avoid.