Balancing the Field: The Dual Responsibilities in Data Contracts
[Originally published in Towards Data Science]
A football game where half the team is unaware they need to score would indeed be a spectacle of confusion and inefficiency. Yet, isn’t this precisely what happens in many data organisations?
Today, numerous data organisations are adopting data contracts as a means to enhance collaboration and drive efficiency. Drawing from my experience in advising companies on data strategy, I have noticed a recurring pattern: while these contracts often meticulously define the responsibilities of data providers — from ensuring data accuracy to maintaining stable schemas — they frequently overlook the role of the data consumer.
It’s as if once the data is delivered, the responsibility of the consumer in extracting value from that data is taken for granted or assumed to be automatic.
Data leaders and professionals who care about business value creation should put more focus on the responsibilities of data consumers. If the consumer does not efficiently analyse, interpret, and apply the data within the context of their business, the data contract isn’t living up to its full potential. Therefore, a truly effective data contract should also detail the consumer’s obligations, ensuring that they are equipped and ready to leverage the data as envisaged.
As we delve deeper, we will examine how neglecting the consumer’s commitments can reduce the business impact of data contracts. And more importantly, we will explore practical measures to incorporate such commitments, fostering a business value-first approach within data programs.
Beyond Compliance — Envisioning a Broader Role for Data Consumers
In the relatively scant literature that addresses consumer commitments within data contracts, there’s a distinct emphasis on risk and compliance. The descriptions lean towards outlining preventive measures and ensuring lawful use, rather than fostering a proactive approach to value creation. Key points often include:
While these obligations are essential for protection and compliance, they often place data consumers in a passive role. Recently, I spoke with a Chief Data Officer at a utilities company who shared an enlightening example. They had just implemented self-service capabilities for users to access datasets directly on their data platform, Databricks. This initiative was a technical success, evidenced by a high number of accesses. However, the CDO expressed a common concern: despite the increased data access, there was no clear visibility into the downstream value generated. This scenario is a prime example of the disconnect that can occur when the focus is solely on providing access, not on how that access translates to business impact.
To truly leverage data as a strategic asset, we need to extend our vision beyond these restrictive frameworks. The next section will delve into how the narrative and structure of consumer commitments can be transformed to encourage a more dynamic and value-oriented use of data.
Respecting the Producers — Committing to Value Creation
Commitments in data contracts come with their share of overhead. For data producers or data product owners, this means an ongoing investment in maintaining data pipelines, ensuring data quality, and providing the necessary infrastructure. While these tasks are critical, they can become costly, not just in financial terms but also in opportunity cost. It’s time to examine the consumer side to understand how these commitments can translate into tangible business value — or fail to do so.
Imagine a scenario in which an intern or employee between assignments gains access to a data product for a project that doesn’t take off. The project is shelved, but the data product remains active, maintained at a cost, and ready for use. Although the data may be utilised effectively in other initiatives, in the context of this failed project, there’s a clear disconnect: the data product is maintained, incurring costs without delivering any value.
Worse still is when a project moves forward, and the data is used to create a new dashboard, only to find that it does not get adopted by the business. The dashboards become little more than digital paperweights, and the time and effort invested in them are wasted.
Even in successful cases where data use initially drives significant business value, the landscape can shift rapidly, leaving once-valuable projects obsolete. For instance, a consumer may leverage data to drive a particular initiative that yields high returns. Over time, however, as business needs change, the value of that initiative diminishes, yet the commitments and associated costs to maintain access to the data persist. The data product continues to be maintained according to the original contract, even when it no longer serves its initial high-value purpose.
These scenarios underscore the need for data contracts to adapt to the dynamic nature of business. They highlight the necessity for data consumer commitments to extend beyond access and usage to include the active pursuit of value generation, efficiency, and adaptability.
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The implications are clear: data contracts need to ensure that on the consumer’s side, there’s not just the responsibility to use data safely and legally but also to use it effectively and pivot as necessary to maintain alignment with business value. The next section will explore strategies to structure data consumer commitments that are flexible, value-focused, and capable of evolving with the business needs.
Scoring Goals — From Data Products to Business Value
The core principle is simple: every data engagement within an enterprise should yield value that surpasses its associated costs. In this context, a data product with solid SLAs, guaranteed reliability, and consistent accessibility is akin to an excellent pass in football — it creates the opportunity, yet the conversion to a goal rests with the data consumers.
In the process of conducting Business Value Creation Assessments, an approach pioneered at Kindata, I’ve come to appreciate the advantage of approaching value generation as two distinct phases:
· Delivery of Business Use Cases: This involves the data consumer crafting strategic reports, AI/ML models, or other analytical tools that inform and empower business decisions.
· Effective Business Usage: The ultimate success metric lies in how these tools are used by the business in achieving both financial and non-financial objectives. This phase often reveals the level of business unit involvement in data programs, a crucial factor in deriving true business value.
Data consumers are at the centre of business value creation. As the ones directly tapping into data products, they are in a prime position to ‘score the goals’ — that is, to deliver business value. Recognising their pivotal role means also understanding the need for accountability in how they utilise these data resources.
To foster this culture of accountability and ensure that data consumers are not just participants but active value creators, your organisation can adopt a structured approach with formalised data consumer commitments:
1. Document Data Usage: Record every interaction with a data product, specifying its purpose. Clarity at this stage sets the foundation for accountability.
2. Measure Outcomes: Regularly measure how the data products influence business objectives. This includes not only the delivery of business use-cases but also the ongoing engagement with business sponsors to make sure the value is actively realised through time.
3. Feedback to Data Producers: Share success stories where data products have significantly contributed to business outcomes and identify opportunities for further improvements.
4. Release Unnecessary Commitments: As a data consumer, when you determine that a data product no longer serves your purpose, promptly inform the data producers to release them from their obligations. This crucial step ensures resources are reallocated efficiently and maintenance efforts are not wasted on unused data products.
By embodying these practices, data consumers become proactive agents of value creation, ensuring data products consistently align with and contribute to the business’s overarching objectives. Of course, understanding these commitments is only the starting point. They need to be operationalised through the right combination of culture, governance and tools.
Data products and data contracts are great ways of organising data teams and adding the extra focus on consumer commitments can make a significant difference.
Just as in football, where every team member must be aligned with the objective to score, in the realm of data, clarity of purpose is equally critical. We cannot hope to win if a substantial part of our team doesn’t understand that the endgame is to score goals — to generate business value.
So, as we refine our playbooks and sharpen our strategies, let’s not lose sight of the goalposts. After all, in the game of data-driven success, it’s the goals that count.