Data quality assessment
- A short term, cost efficient way to get a handle on data quality issues
- Solution recommendations that will address data quality challenges and enhance your bottom line
- A business case for a new or expanded sustainable data quality program
CASE STUDY:
New Zealand
King Salmon
“It’s important to have business partners that you trust and Indigo have always presented an honest and no nonsense approach.”
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Talk to us if you want to evolve your business information systems to world-class standards.
Data quality issues can impact heavily on the performance of your business or organisation. Reports are incorrect; important decisions are based on flawed information; analysis is meaningless, because base data is wrong. You might be losing customers every day, as you fail to accurately identify customer purchase history and product preferences, or even the spelling of their names.
Here are some more examples of how poor data quality drives failure:
- Flawed sales product inventory and production forecasting
- Billing and payment errors that hurt your ability to accurately state your financials
- Inability to confidently track financials, because you can’t balance or reconcile financial data sourced from multiple systems
- Loss of customers due to an inability to track customer interactions or to recognize high-status customers
Indigo’s data quality assessment service can help you to reduce costs by addressing the quality of data that supports your key business processes. It also can maximize the return of your corporate investments, such as the implementation of large new applications, and help you to meet compliance and regulatory requirements. In the long term, it can improve customer and industry perceptions of your business or organisation.
When assessing data quality, we focus on four critical areas:
Data usage
- Can you meet and track your KPIs using existing data?
- Can you effectively support new and changing business processes, which might be driven by mergers and acquisitions or new enterprise priorities?
Data movement
- What cost is incurred due to the inability to reconcile financial data back to its sources?
- Do you have to make business decisions based on data that is clearly inconsistent with its original source?
Data sources
- Do you struggle with inconsistent and redundant data? How does this impact customer service, product provisioning and the quality of reporting?
- Do you have a single source of the truth, or a validated system of record?
Data business rules
- What is the business cost associated with incorrect or poorly defined data?
- How much is data rework costing?
- How much time do you spend debating common definitions and usage of data?
CASE STUDY:
Pumpkin Patch
“Now the business can make quicker decisions because they’re working with trusted information.”
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