Data Governance
What is Data Governance? RK
Talend (2021) defines data governance as “a collection of processes, roles, policies, standards and metrics that ensure the effective and efficient use of information in enabling an organisation to achieve its goals”. There are two key purposes to data governance - increasing the value of data collected, and minimising risks and costs associated with the collection of data (Abraham, Schneider & Vom Brock, 2019).
There has been an exponential growth in the data managed by organisations in recent years. Did you know that big data is estimated to be worth $77 billion by 2023? (Balkhi, 2019). Organisations are collecting more data than ever before which brings with it numerous challenges. Fashion brands today collect data from multiple channels including ecommerce stores, brick-and-mortar stores, and a multitude of different devices.
In order to be effective and efficient, data collected must be secure, timely, accurate, compliant with industry and data regulations, well organised and accessible to only the relevant individuals within the business. This can seem like a mammoth task for any business to take on, which is why we advise the implementation of a data governance strategy and framework for our clients.
Prior to designing and implementing a data governance framework, Chernesky (2019) advises that an organisation must assess firstly, whether a data governance framework is necessary to operate in line with data regulations, secondly, whether a framework can give quicker insights to data analytics and thirdly, whether a data governance framework will help with reducing time, cost and risk for the organisation.
Creating a data governance framework offers many benefits for an organisation. According to Talend (2021), potential benefits include improved data quality and management, consistent compliance with data regulations along with ensuring data is easily accessible to only the appropriate parties. For example, businesses in Ireland and the European Union must handle data in accordance with the GDPR which was established in 2018. A clear data governance framework and strategy can assist organisations in adhering to these regulations and prevent data loss and theft. (Read our recent article on GDPR here). Furthermore, ensuring the integrity of data is crucial for organisations and a Data Governance Framework can play a key role in ensuring data collected is accurate and effectively managed so that it is “clean, accurate, usable and secure” (Aga, Arbanas, Dejong & Sutter, 2021).
There are essential steps in establishing a data governance framework which include, defining the goals of data governance, establishing a data governance team and deciding on which framework model to use; top down, bottom up or collaborative. Mustimuhw Information Solutions Inc. ( 2015), offers a comprehensive list of six essential elements for an effective data governance framework, as outlined below:
Data governance vision and principles
Governance structure
Accountability mechanisms
Data governance policy
Privacy and security policy
Legal instruments
At Group Fashion Agency, our team can assist you at every stage in designing and implementing a Data Governance Framework for your organisation. Contact us today to find out how we can help.
#DataGovernance #DataGovernanceFramework #BigData #Fashion
Bibliography:
Abraham, R., Schneider, J. & Vom Brocke, J. (2019) “Data Governance: A Conceptual Framework, Structured Review and Research Agenda”, International Journal of Information Management DOI: 10.1016/j.ijinfomgt.2019.07.008
Aga, G., Arbanas, J., Dejong, C. & Sutter, D. (2021) “Deloitte. Treat Your Data Like the Superpower it is: Making the Case for Date Governance” [Online Article] Available at: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/finance/us-rfa-data-governance-program-tmt-companies.pdf [Accessed 28th March 2021].
Balkhi, Syed (2019) “How Companies are Using Big Data to Boost Sales, And How You Can Do the Same”, [Online Article] Available at: https://www.entrepreneur.com/article/325923 [Accessed 28th March 2021].
Mustimuhw Information Solutions Inc. (2015) “Data Governance Framework” [Online Article]. Available at: https://static1.squarespace.com/static/558c624de4b0574c94d62a61/t/558c75a5e4b0391692159c81/1435268517023/BCFNDGI-Data-Governance-Framework.pdf [Accessed 28th March 2021].
Chernesky, R. (2019) “Four Steps to Building a Successful Data Governance Team: An Objective Focused Strategy for Data Governance Success” [Online Article] Available at: https://www.infogix.com/four-steps-to-building-a-successful-data-governance-team/ [Accessed 28th March 2021].
Talend (2021), “Definitive Guide to Data Governance”[Online Article]. Available at: https://www.talend.com/resources/definitive-guide-data-governance/ [Accessed 28th March 2021].


Data Governance is the authority and control over the management of data assets. When carried out effectively, data governance leads to improved data quality and a reduction in data management costs. Gregory (2011) explains without strong data governance in an organisation, failure to provide effective corporate governance and compliance will open up the risk of the organisation being open to failure.
ReplyDeleteHaving an effective Data Governance strategy is fundamental for businesses to be true data-driven companies. Having a strategy benefits companies in a number of ways.
It offers Marketing Teams access to customer data from transactional systems, resulting in access to historical information that aids them in developing personalised marketing campaigns. It is also central in the access, tracking and sharing of core metrics to inform their analytics teams accurately and effectively.
• Gregory, A., 2011. Data governance — Protecting and unleashing the value of your customer data assets. Journal of Direct, Data and Digital Marketing Practice, 12(3), pp.230-248.
Data Governance Common Challenges | RM
ReplyDeleteMany businesses still face challenges with data governance management.
1. Lack of skilled staff to conduct data analysis can create a barrier to effective data governance, hidden patterns and unknown correlations are important to identify.
2. With poor quality data, effective decisions cannot be made.
3. The number of data regulatory requirements is increasing making it harder to respond with the lack of a clear data governance structure.
These challenges can be addressed by organisations that employ a multistage approach with a well designed data governance foundation with appropriately implemented data architecture.
References
Rethinking Data Governance and Data Management, 2020.