Data governance as an enabler: Agile data governanceMohammad Syed
As data & analytics becomes even more federated, CDOs need to reduce the bureaucracy of data governance and focus instead on supporting value delivery. In this blog post, we explore how agile data governance can support with this process.
The need for data governance
Today, businesses realise that data holds the key to understanding their customers, finding new opportunities, and increasing operational efficiency. As organisations become more data-driven, data governance helps to provide accountability and a decision-making framework.
In a perfect world, data would be managed as a strategic asset. It would reconcile the goals of the CDO with those of the business to deliver high-quality data in real-time to a “cognitive enterprise”, capable of rapid innovation whilst simultaneously maintaining compliance to data regulations. However, even forward-thinking organisations that invest heavily in a modern data architecture often ignore the human element: formal accountability and governance of data. As a result, they are often left with a slew of exciting opportunities that are hindered by a lack of data quality.
To address this issue, there are two common, although limited, approaches that are often adopted by such organisations:
- Kickstart a parallel data governance programme to create new data governance capabilities, hoping that they will support valuable analytics programmes in future.
- Focus on delivering valuable analytics programmes and allow them to manage data as they see fit, retrospectively formalising data governance and resolving data issues at a later date.
However, these approaches can be problematic. The first approach normally starts with business strategies and hierarchies rather than solutions, which have much clearer outcomes, whilst the second approach encourages a parochial, insular view of data. In addition, many organisations simply move data into lakes with a vague notion of value and without any formal on-boarding or governance process in place for new data. Such processes are often viewed as onerous.
Modern data culture
The goals of data governance are noble and necessary, but programmes often stifle innovation and drain resources. Many organisations get tied up in committees and artefacts, whilst data fails to improve.
Traditional approaches to data governance are no longer feasible for modern, data-driven enterprises working at scale, as new paradigms are replacing long-held assumptions about data. In short, a new data culture is emerging, to which data governance must adapt:
- Responsibility for data is shifting to the business, as all employees become empowered to create and use data with limited IT involvement to create a true “data-driven” culture.
- Data architecture is increasingly decentralised away from the enterprise data warehouse/ lake and towards a distributed, dynamic landscape with free-forming agile delivery teams.
- The notion of enterprise-wide, strategic IT solutions is giving way to greater IT federation, as Agile teams use cloud services to procure an ever-evolving plethora of technology solutions.
- Users are no longer ‘representing’ data but creating their own datasets to support highly bespoke solutions with deep business integrations, such as for marketing or customer analytics purposes.
In the context of these changes, and of ever-increasing regulatory requirements, data governance must become an enabler. It should help the business with an infusion of real-time support and reconciling any conflict between the goals of the CDO and the business. For example, whilst the business might want low-touch, continuous support for projects and data of known value, the CDO may wish to see that enterprise data is improved through minimum standards of accountability, availability, and utility. So how can we bridge this gap?
How can data governance truly enable rapid value delivery? Enter agile data governance
Agile data governance reimagines data governance in the spirit of Agile delivery and DevOps, operating as a community of practice to support agile business teams to rapidly deliver value. It also ensures that enterprise requirements for data management are met across all of these agile business teams.
Abandoning the 'shelf ware and ivory tower' approach of traditional programmes, the office of the CDO mobilises agile data governance to provide real-time integration and collaboration across the enterprise. It actively supports business teams to resolve issues and maximise the value of enterprise data management services, such as metadata repositories, by harmonising data across business teams:
This business-led and value-focused approach instils a 'you create it, you own it' data culture, based on a 'definition of done' from the CDO’s office, and provides a level of accountability rarely seen in traditional data governance programmes. In this way, the CDO can ensure that best practices can be cascaded into business teams without interrupting delivery, as well as ensure that data-related decisions are made with an enterprise-wide perspective and with the appropriate governance.
We recommend that CDOs identify significant analytics projects already underway and use them as a test bed for agile data governance, forming a community of practice to operate as a value-enabler. By doing so, the CDO can better connect to the 'shop floor,' which will provide a basis for more clearly articulating demonstrable value to the C- Suite and enabling them to make a case for investment in enterprise-wide capabilities with more evidence.
Business leaders may well have been left feeling frustrated with previous data & analytics initiatives, particularly if they failed to resolve deep problems such as a lack of data governance. Offering real-time support for their most critical projects will leave them inspired and, in exchange, they will be more willing to act as 'good data citizens' for the enterprise's critical data.
In a nutshell
In a fast-paced world, the demand for new insights and innovation is urgent and constant. Help the business operationalise data governance in the spirit of Agile and DevOps and use the demonstrable benefits to build a case for the enterprise capabilities that are so desperately needed.
If you would like to learn more about the topics discussed in this blog post, please get in touch with one of our experts.
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