Data Product Managers: Lead the Shift from a Data-Last to a Data-First Approach

This post was guest authored by Shivani Srivastava as part of our series with thought leaders on Continuous Product Design.

Shivani Srivastava is a product management leader with extensive experience in transforming consumer marketing and digital experiences with data-driven solutions. Drawing from her experiences leading data product management, Shivani helps readers evaluate and formulate a data-first strategy.

The role of data in a world of instant experiences

The digitization of our world has led to streams of data generated from our clicks and interactions over mobile apps, websites and IOT devices. Consumers are equipped with a great deal of information and infinite choices in products and experiences. An average 18+ years old US consumer spends 7 hours and 30 minutes daily on digital media, according to Statista 2020.

Over time, consumers have learned to expect instant and personalized experiences in their interactions with brands. As a result, every part of the business has become more data-driven. Data is the new oil.

To keep up with the rapidly changing business landscape and consumer expectations, we need a mindshift to care for data throughout the process of designing new products and consumer experiences. This requires a strategy to collect vital data to not only measure product and business KPIs but also gather deeper insights about our customers.

The poor state of digital data management

There are plenty of tools to harness the data that is growing by leaps and bounds. These tools are very useful in knitting together the story of consumer’s interaction with the brand. However, many companies struggle in producing a real-time, integrated view of their consumers.

Adding new tools without a well-thought data management practice has aggravated the problem with multiple versions of truth or silos of data. This has resulted in delayed and partial insights that negatively impact product strategy, design, and measurement. It has real business implications with missed opportunities to engage consumers in a timely manner and increase business value.

As data product leaders, we have to establish a single source of truth about consumers by optimizing and integrating our tools and processes.

Are you ready for a Data-First approach?

The demand on data is growing, especially with the shift towards agile product development and experimentation. In order to support continuous product design and delivery , a strong data foundation is needed. This requires a shift from data as a byproduct, to a well established data product management practice to leverage data as an asset.

To help you evaluate your organization’s data maturity level, start by answering the question below.

Assess your data maturity:

1. Is it hard for you to track business KPIs in real time? Are you dependent on a few data specialists to cure the data and produce ad hoc reports?
2. Do you have too many data sources to track similar information and confused on which one to rely on?
3. Is your product development lifecycle and measurement impacted by lack of timely data availability?
4. Have you been wondering why the data breaks so often and impedes insights and measurement?
5. Are data scientists and analysts spending 20% or more time on data manipulation and integration efforts?
6. Are you unable to keep up with the rising internal demands for real time data to analyze and measure digital experiences?

If you answered ‘Yes’ to three or more of these questions then it may be time to rip the band-aid off between multiple, fragmented data solutions and put a strategy together to care for data.

Formulate your strategy for a solid data foundation

This requires redesigning your organization, processes, and technology to establish a solid data foundation. This is no easy journey, and requires stakeholders and executive alignment, organizational commitment, and budget. The following is a high-level guide to help you formulate your strategy:

People

1. Formalize data natives into dedicated roles to manage data strategy, architecture, governance and administration as a central function.
2. Create a culture of self-service and educate the organization on data, tools and the power of data-driven decisions.
3. Make producers of data and insights accountable for data quality and drive alignment towards a single source of truth.

Process

1. Identify key data elements, and create a well-defined metadata strategy that is accessible to the organization for self-service.
2. Treat data as a product and apply product development rigor to innovate and manage data as a business asset.
3. Reject user stories without proper measurement strategies. Define data specific checkpoints throughout the development lifecycle.

Technology

1. Introduce cloud computing and/or big data platforms with ability to accommodate and process high volume and high velocity data from multiple sources.
2. Integrate data sources to create a ‘single source of truth’ of the customer and their activities with microservices and APIs available for universal data access.
3. Leverage governance tool to proactively manage data quality and user access. Have procedures to protect consumer PII while supporting self-service culture.

Data is the fuel for growth. Your entire organization needs to care for data as a critical asset. By building awareness and holding your organization accountable, you can help lead the change from a data-last to a data-first culture.