In this episode, Jason talks to Benny Clive Benford who until recently was the Chief Data Officer of the Jaguar-LandRover (JLR) group and is now giving executive level guidance to large corporations all across the globe.
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Data does nothing by itself. It is all about having clever people with the right tools and the right processes to drive true change within an organisation.
00:40 Benny’s journey in data
02:44 What does success in data actually looks like
10:40 Restructuring organisations at scale
13:36 Should the data team be the function that drives organisational restructuring?
16:12 The difference between data as a function within an organisation and data as an asset
24:32 Blending technology teams with other areas of expertise and do so at the right pace
34:33 Putting in frameworks that can help to facilitate change
36:51 Looking at who defines standards
38:11 Does a lack of guidelines stem the success of data as a profession?
Implementing change within an organisation can be a complex and challenging process, especially when it comes to modernising technology and processes. However, leveraging data can help facilitate measurable change and make it easier to achieve.
Many businesses are still using outdated technology from several decades ago, which can slow down operations and hinder productivity. By utilising data, organisations can identify areas where improvements can be made and implement changes that lead to more efficient and effective workflows. For example, data analysis can help identify bottlenecks in supply chain operations or areas where automation could streamline processes.
Despite the potential benefits of using data to drive change, many people may not be interested in data itself. However, by emphasising the ways in which data can enhance their work and improve outcomes, organisations can encourage greater adoption of data-driven processes.
One of the advantages of using data to drive change is that many businesses do not currently consider it as an asset. This means that there is a significant opportunity to leverage data to identify inefficiencies and make improvements. Additionally, modern technology has made it easier to break down data silos and transform disparate data into more useful insights. With the right tools and techniques, organisations can use data to uncover valuable insights and drive positive change within their operations.
Organisational restructuring can be facilitated by leveraging data, whether it involves breaking down information silos horizontally and vertically or completely transforming the structure of the organisation.
Agile is a way of working that emphasises flexibility and responsiveness to change. It can be particularly useful when implementing changes facilitated by data.
The data team can play a crucial role in organisational restructuring, especially when it is integrated into the transformational team. Data teams have the expertise to identify transformational insights and are constantly innovating and testing new ideas. It makes sense to involve them in discussions that require transformation.
The evolution of data teams has been driven by the need to split up roles to manage increasingly complex data infrastructures. However, there is some debate about whether data is a profession in its own right or if it should be integrated into other areas. The Data Management Association (DAMA) is one organisation that seeks to provide a framework for data management as a distinct discipline.
Data plays a crucial role in modern organisations, serving a range of functions and contributing to various aspects of business operations. The four main roles include:
Data transformation: Data can be used to drive transformational change across the organisation, from marketing to operations. By leveraging data insights, organisations can identify inefficiencies and opportunities for improvement and make informed decisions to drive change.
Data and the workforce: Data can help organisations transform their processes and operations to drive more value. By leveraging data insights, organisations can identify areas where automation and innovation can lead to increased productivity and better outcomes.
Data monetisation: Data can be a valuable asset in its own right, and organisations can leverage it to drive revenue and growth. By developing a data monetization strategy, organisations can identify opportunities to monetise their data and create new revenue streams.
Data brand: Data can also play a crucial role in building a brand and reputation. By emphasising data privacy and security, organisations can build trust and establish a competitive advantage. Equally if an organisation is in a position to monetise data externally then the data (or insights) can become part of the brand, think Facebook and its data about people.
While data is often associated with technology, it is important to recognise that it touches upon a range of other areas, including ethics and governance. Effective data management requires a broad range of skills and expertise, including technical and analytical skills, as well as an understanding of business strategy and ethics.
It is also important to recognise that while data is often used as an enabler of technology, it can also be used as a tool to drive change in a range of areas, from marketing to operations. By recognising the transformative power of data and leveraging it effectively, organisations can drive growth, innovation, and success.
Facilitating transformational change in data is a multi-faceted process that requires careful planning, effective communication, and a willingness to adapt to changing circumstances. Focusing on the iteration of outcomes is crucial, meaning that clear goals and priorities must be set, a strong foundation built, and a balance struck between quick wins and maintaining momentum.
To ensure success, the team’s ability to facilitate change effectively is essential. It’s necessary to have the right mix of skills and expertise, and to ensure team members are aligned around common goals and objectives.
Different teams require different forms of transformation. As such, it’s important to recognise their unique goals, objectives, and organisational context, tailoring transformation efforts to meet their specific needs and priorities.
There is a lack of professional maturity in the data profession, with many roles not clearly defined and a lack of standards around what constitutes the role of a data professional. This can lead to confusion about who does what and can hinder the effectiveness of transformation efforts. With the emergence of AI, there is a growing need to define roles and establish standards to ensure that data professionals can effectively leverage new technologies.
Ethical considerations are crucial to the success of data-driven initiatives. It’s important to define the ethical principles that should guide the development and use of AI and other emerging technologies.
Standards also need to be put in place to ensure that data professionals can take full advantage of the opportunities available to them. Establishing clear standards can create a shared language and understanding of the role of data in the organisation, enabling teams to work together more effectively.
Data plays a critical role in organisations today, and the effective use of data can drive significant value and transformational change. However, organisations must consider various factors to leverage data successfully, such as setting clear goals, building a strong foundation, and striking a balance between quick wins and maintaining momentum.
By taking a holistic approach and considering the unique needs and priorities of different teams, organisations can leverage data more effectively to drive organisational success.