Data engineering and storage costs are rising rapidly, with a 30% increase in 2022 (US and European cloud prices set to soar in 2023 – Techzine Europe). As US and European cloud prices were set to soar in 2023, data leaders searched for ways to maintain delivery speed while improving data governance and managing budgets. Enter Data Products!
In this blog, we’ll guide you through creating a data product-focused data strategy. We’ll cover key concepts like defining data products, setting up domain-specific teams, and implementing a federated ownership model to enhance data management and efficiency within your organisation.
Are you looking to write a data strategy but unsure how? Read our guide on how to write your data strategy for further information.
What is a Data Product?
Data products are reusable assets that deliver trusted datasets for specific purposes, ensuring the right data reaches the right people in the right format. The unique aspect of data products is the federated ownership model, where domain-specific teams manage their data from production to consumption, ensuring better efficiency and responsibility.
Domain driven ownership
Figure 1 A Domain-Oriented Ownership model
Source: https://www.starburst.io/blog/data-mesh-and-starburst-domain-oriented-ownership-architecture/
What is a Data Product-Focused Data Strategy?
A data product-focused data strategy involves creating reusable data assets, known as data products, to solve specific business problems. This strategy enhances data quality, reduces silos, and improves security through an ownership model.
It shifts the approach from treating data as an output of projects to managing data as products, ensuring ongoing maintenance and updates. This strategy includes defining domains, building data products, and continuously engaging with consumers to improve and deliver valuable data solutions.
Why Do You Need a Data Product-Focused Data Strategy?
In today’s data-centric world, having a solid data product strategy is a necessity for your organisation.
- Improves Data Trustworthiness: Ensures accountability for data quality through domain ownership.
- Reduces Data Silos: Facilitates autonomous access to managed data, enhancing self-service capabilities.
- Enhances Security: Allows domain teams to manage access and compliance, optimising risk management.
- Supports Continuous Improvement: Encourages ongoing maintenance and updates of data assets.
- Drives Business Value: Focuses on solving specific business problems, leading to more impactful data solutions.
Read our blog to find out more information about the purpose of a company’s data strategy.
Is the Data Product Approach Suitability for Mature Data Estates?
The data product approach may not suit less mature data estates due to its reliance on advanced processes, skills, and infrastructure. However, adopting it as a long-term goal can improve existing practices and lay the groundwork for future data product delivery.
How to Integrate a Product Data Strategy into your Organisation
Incorporating a data product approach into your data strategy has people, process and technology implications – so the following tips are designed to provide you with some ideas of steps you might want to take if you are considering taking the plunge.
We mentioned earlier the concept of domain driven ownership. Given the nature of data products being focused on how each domain can solve issues for the business, your first port of call is deciding how to divide the organisation up into domains.
A good starting point for this is to investigate the existing subject areas that sit within your data estate – most organisations will have these. Once you have a picture of what your domains are, you can start to look at the process of building a data product.
If your data strategy is led by IT or Data, this is where you start to find friends in the domain areas. Once you have identified a domain that is open to the data product approach, you can work with them to define the data products that would support the business needs from that domain.
When pitching a product, it must solve a specific problem. Data products are no different. Start by identifying and addressing business challenges.
Key Steps to Build Data Products
You don’t see people on Dragon’s Den pitching a product that doesn’t solve a specific problem. In fact, the most successful companies will think about the problem first and work to build a solution to that problem. Data Products are no different, and building a strategy for these data products should align with that view.
You will want to build products that solve specific problems and challenges within the business, which can be marketed and maintained.
Understand Consumer Needs
Get to know your consumers, do your research, understand the pains they feel when engaging with your data.
Establish Feedback Processes
Establish processes that enable consumers to contact and feedback to data product teams so that every data product is built either toward solving a specific problem or responding to market demand quickly by creating new business opportunities.
Prioritise
You can then set out a prioritisation exercise to understand where to focus efforts to deliver your first data products!
Why Should You Take the Lighthouse Approach to Data Strategy?
As with any new process within an organisation, at Oakland – we find that delivering value rapidly is critical. We can do this by taking a lighthouse approach, where you take a narrow but deep slice of your data estate and design a small but valuable data product.
Luke Sharma, Senior Data Consultant at Oakland, states
‘’We achieve this by taking a lighthouse approach, where we focus on a narrow but deep slice of our data estate to design a small yet valuable data product. This method allows us to set up the rituals and roles of product management to fit within our existing operating model. Once the lighthouse project is delivered, we assess the supporting processes and roles, as well as the value gained from the product.’’
He goes on to mention that, ‘’These learnings are then embedded into our Target Operating Model, ensuring the product management approach is integrated into the organisation’s ways of working. The key here is that the approach is tested and drives value for your organisation with a more moderate investment. This lighthouse data product and way of working can then be demonstrated to other domains, increasing appetite and excitement.”
Breaking the Project Mindset
This is where the strategy element of “data product strategy” becomes vital because it involves cultural and process change. Once you have delivered a data product, you can rapidly see it fall back into the traditional cycle of standard data development because the organisation’s mentality hasn’t moved forward with the technology.
Data is unfortunately often seen as an output of a project, be it a report, dashboard, or ML algorithm. The project is delivered, signed off by stakeholders and then handed over to the business unit. Inevitably the deliverables from these projects are outdated pretty quickly – and the response? Set up another project, build another report – rinse and repeat.
You need to stop thinking of data as an output and start to think about data as a product.
“Products need to be maintained, updated, and associated with SLAs/data contracts that guarantee a certain level of uptime and data quality as part of a standard product lifecycle, managed by the product management team. By taking the approach learned from the lighthouse project and embedding it into a Target Operating Model (TOM), we ensure that accountability for data product maintenance is prioritised.”
Luke Sharma, Senior Data Consultant
The whole aim of data products is they are built and maintained in order to be reusable, shareable assets!
Focusing on Value
Data products must deliver specific outcomes. Engage with consumers to understand their needs and guide product development.
Using data products in your strategy will drive adoption and accountability within your organisation. Engage regularly with consumers to refine and prioritise data products, overcoming technological and process complexities.
For more information, contact us at hello@theoaklandgroup.co.uk. For the original blog post, visit Oakland Blog.
