For Software Companies

by | Mar 28, 2023

The support desks of software suppliers spend a significant proportion of their time dealing with issues arising from poor quality data entered into their systems, when they could be using their time more productively. Addressing data issues at outset reduces these calls and leaves their clients with a better impression of the software and its supplier.

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For Software Companies

Poor data can create problems in multiple areas

Support calls

Support Calls

time spent on data related issues can impact service levels

System investigation

System investigation errors

data issues can impact on development capacity

Client relationship

Client relationship

confidence in systems can be eroded by poor quality data

Reputation damage

Reputational damage

regulatory issues arising from poor quality data may reflect badly on providers

The consequences of bad data can be significant:

  • Damaged client relationships leading to loss of high net worth clients
  • Lost reputation if the above happens at any scale
  • Increased staff costs due to additional resources required to monitor and resolve data related issues
  • Reduced productivity continuously allocating valuable, and often limited, resource to address data problems
  • Regulatory fines could occur if customers data is misrepresented or regulatory reporting is inaccurate
  • Strategic decisions made based on poor data can be damaging to both clients and the firm
  • Cost of compliance will grow if data issues are ignored
While software companies can reduce the incidence of bad data in their clients’ systems via functions such as look up tables and four eyes checking, they have no control over the quality of the input. By helping clients to maintain the quality of their data, and system set up, software companies can establish and retain their trust.
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To find out how to avoid these pitfalls

DCI Data Analyst Screenshot

Insights for Software Companies

DCI The hidden cost of bad data

The hidden cost of bad data

Regulatory Imperative

Regulatory imperative

Bad data pain points

Pain points from bad data