In our personal life as well as professional ones, we are being inundated with an increasing amount of data. While this might just prove to be a minor inconvenience in most cases, if such huge amounts of data is not managed properly at the business level, the long term impact could be significant. But if you are not sure about the quality of your data, how do you manage it? Instead of getting defensive about your processes and ideas, let the data tell you if it is up to the mark.

Here are three questions that you should ask your data the next time you are in the same room –
 

1. Are you complete? – While this might sound like an existential question, it is a critical part of judging your data quality. Many a times, during our projects, we have found that the data itself was incomplete. This can happen due to many reasons including human error and system failures. Sometimes, you might have incomplete data because you were not aware that you needed more information. This can be sorted out quite easily (even though it might take time). You need to re-evaluate your data requirements and calibrate the complete process. E.g. if your system does not have the value for the internal diameters of a particular valve you use in your plant, the decisions you will take on the basis of this incomplete information might be wrong.

 

2. Do I understand you? – It is critical to understand what your data is trying to tell you. The same piece of information might signify different things to different people. What you need to make sure is that you do not misinterpret the data presented to you. Ask the right questions to the right people at the right time and you will minimize the chances of misunderstanding the data in your system.

 

3. Can I trust you? – This will probably be the most important question in your conversation. The reliability of the data you need to use has to be unquestionable. A large proportion of data quality issues arise because the data was not reliable in the first place. If you cannot ensure the trustworthiness of your data, it is bound to impact your process and your business down the line. Put a data governance system in place to keep the data clean on an ongoing basis. E.g. a data governance system such as Verdantis’ Integrity puts in place a robust workflow or the creation of a new item in the database. This ensures that any data on a new part that you are getting is reliable and up to date.

Data has become a critical asset for organizations and it is affecting every facet of business. Improving your data quality and ensuring it remains that way is now essential for any company looking to make a mark in the market. What have been your experiences regarding data quality? Is there anything else you would ask of your data? I would love to read your views in the comments section.

Further Reading –

Blog – Data Governance Implementation – What you wanted to ask but couldn’t

White Paper – Material Data Quality Project Handbook – Avoiding Pitfalls

Case Study – Material Master Data Management for a leading Oil and Gas Company

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Vipul Aroh

Vipul Aroh is a part of the Marketing team at Verdantis. Although relatively new to the field of master data management and data governance, he is fascinated by the topics and is becoming more passionate about them by the day. Vipul holds a Master’s in Business Administration from Sydneham Institute of Management, Mumbai.

Latest posts by Vipul Aroh (see all)

• Key Takeaways from our Webinar – Strategically Manage Data Quality in an ERP rollout - November 4, 2015
• Boosting the ROI of an ERP project – Part I - August 31, 2015
• Master Data Quality Improvement – Adding to your EAM Implementation ROI - July 29, 2015