Data Leadership Extends Beyond Core-Data Professionals
Core-Data Leaders, Business Data Leaders, and Enablement Strategies to Lead with Data In the face of Low Data Literacy or Analytics Training
This piece is a community contribution from James Miller, a seasoned data, strategy and commercial leader who bridges the gap between data and business. He began his career in retail analytics and has since worked as a Director of Data and Analytics, Chief Data Officer, and Strategy Consultant. James has extensive experience as both a strategic advisor and in-house leader, developing strategic and operational data and analytics capabilities. He has led and built propositions at FTSE 50, 100, and 250 organisations, as well as start-ups, and has supported the transformation of many high-growth and global brands. We highly appreciate James sharing his insights with the MD101 community.
(includes a cameo from our very own Travis Thompson)
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Why Data Leadership is Broader Than You Think
If We Believe Data Is an Asset, Then Like Any Asset, It Must Be Led.
Since the emergence of the first Chief Data Officers a little over twenty years ago, we have seen an incredible rise in professionals stepping up to do just this. I began my career in data about the same time these newly minted CDOs made their debut, and I’m part of the generation who took data from the backroom to the boardroom.
This allowed me to witness the rapid evolution of data leadership, from its beginnings in largely regulated industries where the focus was squarely on data management and compliance to where it is today, spanning the entire data value chain.
Over the years, I’ve had the opportunity to work and engage with hundreds of data leaders from diverse backgrounds and varying levels of responsibility. This has given me plenty of time to reflect on an important question.
What is data leadership, really? (and who are the data leaders in our organisations?)
Who is a Data Leader? Let’s Start Simple with a Straightforward Definition.
The role of a data leader is to ensure data is harnessed as an asset, driving value for an organisation. Without accountability, sponsorship, evangelism, and application of leadership, it is not possible to properly manage and drive value from data.
The Core-Data Professionals: By the Nature of Data, Data Leadership Often Expands Beyond Executives
When we think about Data Leadership, most of us picture the Chief Data Officer, a C-suite level operator, the ‘uber’ data professional responsible for the strategic direction of data. Yet, CDOs are far from ubiquitous and only a part of the data leadership at the top of a much larger pyramid of data roles. While many large organisations have CDOs today, many more organisations, particularly smaller ones, do not and might never have one.
This raises an interesting question. Does the absence of a CDO mean an organisation lacks data leadership? Well, in some cases, especially in enterprises, the answer is likely to be yes, but in my experience, the answer is often a resounding no.
Beneath the CDO is a populous layer of data professionals - analysts, data scientists, data architects, data governance stewards, data engineers, BI specialists, product managers (and many more), who are deeply immersed in the technical aspects of data management and analytics. In many cases, these professionals, often the most senior data roles in their organisations, are effectively de facto data leaders, even if they don’t carry an executive title.
Some may be responsible for critical components of the data value chain, while others manage the entire data landscape of their organisation, irrespective of where they sit in the corporate hierarchy. Here’s the chilling or liberating truth, depending on your perspective. If you are the most senior data person in your organisation, you are the data leader. Even if there is only one of you.
Your organisation could need someone at an executive level, but the fact remains that if you are the most senior data professional, strategic decisions will likely fall to you, whether that is a good thing or not. For many, this is where the definition of data leadership ends, but for me, it’s really where it starts.
Beyond the Core: The Role of Business Data Leaders
If data is really going to fulfil its potential in our organisations, we need to get comfortable with a broader concept of data leadership. In most data-driven organisations, data leadership is indeed broader than just the inner circle of data professionals. It extends into the business itself, encompassing a group I refer to as business data leaders.
While these individuals might not be data specialists, they play an outsize role in ensuring, through their actions and decisions, that data delivers tangible value for their organisations.
Business data leaders are decision makers, change makers, and action takers - often professionals in areas highly dependent on data, like marketing, finance, product, and operations. These leaders are often distinguished by their understanding of how data can inform their strategies, even if they lack a formal data background.
These folks often appear as self-appointed data domain champions. Despite a lack of formal data and analytics training, they have taken informal ownership of data in their domains. These are people who speak most loudly about the importance of data and where data teams often find their first allies within the business.
The truth is, whether a data domain champion or not, an increasing number of senior leaders I speak to, are only too aware of the need to embrace data and understand how it works to be better at the roles. These are typically not people who will ever have enterprise responsibility, but they own critical use cases for data in their areas and, therefore, need to pay close attention to it.
These people may not be professional data leaders, but play a key role in leading the successful application of data in their organisations.
The concept of data leadership extending beyond core-data professionals is not just theoretical; it has practical implications.
After all, data specialists rarely make up more than 3-5% of a company’s workforce. This alone is a strong case for broadening the definition of data leadership to include the rest of the business. The remaining 97% of employees need to engage with data, and many need to show true leadership in how they utilise it.
If we continue to treat data as the exclusive domain of a specialised few, we risk stifling its potential. Effective data usage requires a community of advocates across an organisation. This community comprises data-informed professionals who are confident, knowledgeable, and willing to champion data-driven decision-making in their day-to-day roles.
Here’s How To Think About Business Data Leaders
While the job of data professionals is to manage and analyse data, the job of data-informed professionals is to use it. The more data users who are confident and skilled advocates, the better the organisation’s outcomes will be.
Business data leaders are essential for four primary reasons:
They’re the decision-makers
Most data teams are not responsible for the business decisions that their work informs. It is the representatives of various business domains who apply the insights derived from data and make decisions that drive outcomes.
They’re collaborators
Data-savvy decision-makers bridge the gap between data and its real-world application. These leaders ensure that insights derived from data are effectively integrated into departmental and functional strategies.
Changemakers
This group is the most important agent of data culture. By embracing data-driven decision-making, they are the true proponents and sustainers of organisational data culture. Data culture is of little use restricted solely to data professionals.
Community elders
A strong data community is vital to the success of data initiatives. Senior leaders who embrace data become role models, leading by example and fostering a culture of data-driven excellence.
How to Carve an Easy Path for Business Data Leaders?
*This section is a contribution from Travis Thompson, Chief Data Architect
As James highlights, business or domain data leaders are not formally trained in data and analytics. However, they do have an information ownership and responsibility of understanding data as a strategic business vertical. “They own critical use cases for data in their areas and, therefore, need to pay close attention to it….playing a key role in leading the successful application of data in their organisations.”
This could mean domain leaders, domain experts, or even the up-and-coming SuperTech Leaders in business. Think CMOs, Sales Leads, Strategy Consultants, and so on. While not all of these business-facing roles would take charge of including data as a non-negotiable strategic asset for their business strategy, the ones that do should not feel hostility when stepping into the data landscape.
To enable data for business, core data teams and leaders need to build a friendly and familiar environment for these business data leaders who are, in fact, the champions for the data team - constructing a direct bridge to the big green metrics like revenue, ROI, and ARR.
How can we facilitate data understanding, usage, and consumption for these business data leaders without them having to spend tons of their business hours on understanding the low-level technicalities of data?
Answer First: Productising Data.
Let’s start with the basic question first: What do we need to make data accessible to business data leaders? And if they are, in fact, leading data initiatives and use cases for their domain, how can we shift control of data to them without compromising the sanity of data?
High-level requirements to ensure good XP for business data leaders and the impact of implementing these requirements.
Requirement I: Accessibility & Transparency of Data
Solution: Easy-to-Use Data Consumption Interface.
Impact: Removes any barriers to accessibility and offers a consistent and transparent view of constantly moving data. Access, interestingly, is not just about security or user tag management. If a delivery agent cannot figure out a poorly addressed location, they’ll never be able to access or find your house.
Ensuring Access, therefore, includes ensuring all of the below counterparts:
Discovery: Are my data citizens able to find or navigate to what they need?
Addressability: Discovering is not enough for usability. You’re technically barred from access unless you can use the data. Are my data citizens able to easily address assets to use them?
Understandability: Same as above. Without understanding the data, you cannot use (access) it.
Natively Accessible: Are my data citizens able to leverage the data through the means available to them?
Interoperable: Are my data citizens able to access data assets across the integrated data ecosystem?
Enablement Strategy: Unified Data Consumption Plane like a Data Product Marketplace that ensures rich semantics (for clarity and discovery), ensures interoperability of data assets between domain teams such as sales and marketing, exposes data through multiple consumption formats (native accessibility), and exposes quality-approved and governed data while visibility showcasing the quality metrics and conditions met.
Requirement II: Transparency in Business Metrics and Metric Dependencies
Solution: Global Metric Tree
Impact: Metric trees are a web of associated metrics cutting across the entire vertical of the data’s journey.
How does it help CXOs & associated business decision-makers:
Ability to detect tracks which are fuelling primary business metrics/KPIs
Ability to detect tracks which are pulling down the primary KPIs
Informed calls on empowering or shutting down tracks across business initiatives and technical tracks without the need to be technically savvy or skilled.
Complete transparency and detailed lineage behind all metrics that are pushing the key metrics such as Revenue, Conversion Rate, or #MQLs forward.
Enablement Strategy: Unified Data Infrastructure like Data Developer Platforms.
The unified design is an apt approach for managing data products or a layer of domain-driven data products. Metric trees are projections that sit on top of these data products to be able to consistently project quality-certified metrics and solve this common analytics problem:
I think a lot of data teams run into the problem of, you know, creating metrics within their BI tool, creating metrics within something like HubSpot, or maybe another growth or marketing tool like Google Analytics. And then, you have three different answers for the same question.
~Madison Schott, Sr. Data Engineer
The unified infrastructure aptly works for a data product ecosystem due to its ability to, as the name suggests, unify different flying parts of the massive data ecosystem. There are a lot of data platform organisations that now implement the Data Developer Platform (DDP) standard, the trick is to loop in your best tech guy and understand how well the vendor offerings match against the DDP or unified platform standards. Here’s more on how things unify.
The above were two of the top qualities that facilitate a smooth journey for business data leaders who are not so well embedded into the deep-tech data stack. There are more. We just need to ensure that these qualities were building or adopting as core data teams are functional enough to enable these leaders to actually lead with data with more surefootedness.
Making Data Everyone’s Business
In my experience, the most successful organisations understand that data is not just the preserve of specialists. It is a vital business asset, making it everyone’s responsibility. The implication is that data, like finance or marketing, must be seen as a core business discipline. If senior leaders are expected to have a strong, high-level understanding of these business verticals, then why not data?
Data may be technical, but so too are plenty of other business disciplines, like finance sales, bizOps, or marketing. To be effective and influential, data must be understood at the business level, just like any other core discipline. Ensuring data is understood by the business means a commitment to three things, which I see as pre-conditions for universal data leadership:
Vision
There must be a shared vision for data and how people expect it to align with business objectives and drive valuable outcomes.
Education
People across all levels need to have sufficient fluency in the management and use of data, as required by their roles and responsibilities.
Collaboration
People must interact and collaborate on data at both strategic and operational levels. Business leaders must play an active part in their organisation’s data strategy, as well as daily operations, where their engagement, contribution, and buy-in are vital to the smooth running and impact of data initiatives.
Final Note
One of the greatest threats to the future of data leadership is sticking to a narrow interpretation. Data has made it out of the backroom and into the boardroom, but that is not enough.
Organisations that succeed are those that recognise the value of building a broader base of data leaders—professionals who may not hold ‘data’ titles but understand its power and potential. By expanding the definition of data leadership, we’re more likely to unlock the true potential of data as a business asset.
Data is an asset. It must be led. And everyone has a role to play.
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I would argue that the way we think about data in businesses need to change again:
https://theafh.substack.com/p/the-wrong-mindset-is-killing-transformation