Do you have a data quality problem?

A recent conversation about a large organisation highlighted an interesting question – How do you quickly and easily know that you have got a data quality problem? 

Clearly, you may have a data manager/ data team who are stating that data quality is poor/declining etc. But are they just obsessive-compulsive types who want everything perfect? 

Key symptoms to look out for: 

  • Excessive effort required and time spent collating weekly performance/sales/quality statistics 
  • Customers complaining staff do not know about previous transactions 
  • Some staff creating their own spreadsheet-based data stores (Data Anarchists) 
  • ‘Surprise’ service failures which, on review, were easily predictable and preventable if people had reviewed the data 
  • Staff maintaining their own data stores either because they do not trust the ‘official’ corporate systems or they have data that they believe is needed by the business, but don’t know what to do with it (Data Squirrels) 
  • Disagreements between staff and teams about organisational performance
  • Multiple data warehouses and data lakes, but you still can’t get reliable performance figures 
  • The highly paid data science team spending >80% of their time preparing data for analysis 
  • Difficulty getting a ‘single view of the customer’ (or asset, product, service) 
  • A large proportion of business transformation/ software project budgets eaten up by data migration activities 
  • Repeated failure of data migration activities due to worse than expected data
  • Uncertainty about where the master source of data is and how to update all other data stores when key data entities change 

If you recognise more than a couple of these symptoms in your organisation, then you have almost certainly got data quality problems! 

Perhaps you have operated for some time like this and don’t see the need to change anything – you believe that you are OK as you are. Well, in today’s highly competitive environment, your competitors will all be improving their quality, efficiency and profitability and probably gaining  customers from you. How long will you survive with poor profits, efficiency and quality leading to a declining market share? See this blog post about the benefits of improving data quality 

What can you do if you think you have data quality problems? 

Two reasonable first steps are: 

  • Undertake some data profiling and data quality assessments of key data entities – this will help confirm the size and nature of your data quality issues 
  • Conduct a maturity assessment, such as the sort that we provide, to objectively understand your strengths and weaknesses relating to data quality
  • Enroll in our online data quality training or discuss options with us for in-house training provision

These actions can put you on the path to improving your data quality and improving profitability, efficiency and quality as a result. Can you afford not taking action?

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