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Data moat playbook part 1: identify your competitive edge

Data moat playbook part 1: identify your competitive edge

Robert Balaban
Senior Data Engineer

Data is a resource. For today's fast-moving digital companies, it may just be the most valuable resource they control, one that has been dubbed "the new oil."

Having access to data is a simple fact of modern business. Putting that data to use and exploiting it in ways that add value, is what can separate industry-leading companies from less successful competitors.

One of the most straightforward ways to address proper data use, from collection and storage through usage, is to construct a "data moat." This is an end-to-end way of thinking about data, one that can deliver value for businesses of many sizes and descriptions.

Today, we'll focus on extracting and storing data as part of a data moat. In part 2 of this series, we'll describe the process of leveraging the collected data to drive value. Together, these practices let companies make their data work for them.

What is a data moat?

Before proceeding with a description of how to create a data moat, it's important to understand the term itself. The phrase "data moat" is a relatively new way to refer to an age-old concern for companies: creating a comprehensive data strategy.

A data moat is an umbrella concept that encompasses all data activity. Organizing and using raw information as fuel to advance business goals falls under this heading. This means important tasks such as enforcing data hygiene and maintaining strong data governance are all parts of operating a data moat.

In recent years, best practices around data moats have evolved, because data itself is changing. The volume, velocity and variety of content collected and used by companies increased as big data analytics became a more prominent business priority. Even more recent innovations, such as the rapid growth of generative AI, have prompted companies to adapt their data strategies even further.

Every business will have its own ideal approach to data moat creation and maintenance based on its industry, scale and unique objectives. Whether this means revising an existing strategy or building from scratch, it's an effort the business should undertake as soon as possible.

What's the importance of setting up a data moat?

The value of a data moat takes a few important forms. For companies in heavily regulated fields that deal with sensitive, personally identifiable information, such a strategy is essential from a governance and compliance perspective. Regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the medical field and the European Union's General Data Protection Regulation (GDPR) demand stringent oversight of data, making a data moat a high priority.

In a more general sense, companies with data moats can use the information as a resource in their products and services. A standard approach to using data can involve applying this information to targeting ads and content based on customer preferences, but the most effective data users are simultaneously improving the experience of interacting with their technology.

These are organizations like Spotify, which use data analysis via OpenAI's artificial intelligence algorithms to serve advanced content recommendations based on users' preferences. By serving up highly personalized content, organizations can create positive experiences that stoke loyalty and keep customers locked into the ecosystem.

Netflix is another of these leading data users, with personalization reaching every piece of its app, including push notifications. Its stated goal is to cut down on browsing time, getting viewers to content they'll want to watch, faster. This is possible because of the company's commitment to its data moat.

How do you extract the necessary data for a data moat?

Building the type of data moat that will allow your organization to put its data to effective use means carefully building the strategy component. From there, you can assemble the technology and implement the tactics that will keep your approach strong over time.

This project should have input from team members from throughout the organization. The key stakeholders who should have a voice in the proceedings include:

With the team assembled, it's time to take a methodical approach to building your data moat. The steps, in order, include:

  1. Understand the data landscape

The data moat construction process starts with questions. What is your business model? What kinds of data sources do you have access to, both internal and external? How unique is the information you have access to?

Your company's goal should be to match up its available data resources with its requirements, extracting information that can help pursue your most closely held business goals. Data streams that are unique to you are especially valuable within your data moat, as they represent a potential point of divergence from your competitors.

  1. Analyze the data for competitive advantage

Once you've identified potentially useful sources of data, the next step is to take concrete steps to make that content into fuel for insights. This may involve inviting stakeholders from the product team to determine the best ways to harness data within your service offerings, as well as performing industry research to determine how your competitors are harnessing information resources.

You may determine that there are opportunities to improve the value of your data moat by tapping into new sources of data or adding additional users. You can expand to new departments and introduce data-driven improvements directly into your customer-facing experiences.

  1. Address governance and sustainability issues

One of the key functions of a data moat is to ensure your business's data usage falls in line with all relevant regulations for your sector. This step is to verify that you have sufficient levels of data protection, visibility and governance to comply with wide-ranging laws such as GDPR, as well as more industry-specific frameworks including HIPAA.

Bringing in partner organizations that have received approval from regulatory bodies to assess systems and infrastructure is a way to quickly and confidently answer questions about your readiness to comply. In addition to getting your current data resources in compliance, you can plan around future needs — for example, will you need to improve your systems in the near future to deal with changes such as rising customer numbers?

  1. Invest in continuous monitoring

Advance preparation can only get your data moat so far — you'll also need to plan on regularly revisiting the strategy in the years ahead. Multiple issues can necessitate changes. These include new regulations, moves by competitors and the emergence of novel technologies that require you to adapt the way you collect, store and use data.

Effective monitoring for your data moat involves selecting the key performance indicators (KPIs) that matter most to your business and allow you to determine whether the data is having its intended effect on your operations. Every company cares about different objectives, and goals can change drastically over time — a firm in a growth phase, for instance, may care far more about expanding its footprint than making a profit, before shifting its mindset.

How can experts help you approach your data moat journey?

Getting started with a data strategy is easiest when you work side by side with third-party experts who can provide expert guidance. This may mean embedding members in your team for close collaboration and skill transfer, to make sure your team can carry the data moat effort forward in the years to come.

From the first ideation through the monitoring and assessment phase, your team can benefit from having experienced professionals' opinions as part of your decision-making process. Considering the importance of having a strong data moat, as well as the need to keep up with ever-changing industry norms and best practices, these contributions can point toward a successful future for your data usage.

The Transcenda team, with our years of experience engaging with companies of all kinds, can deliver a tailored data moat experience, one that reflects your organization's exact needs. From customer-facing product improvements to regulatory compliance and beyond, data may touch many areas of your organization, all of which need attention.

In part 2 of the series, we'll focus on the specific roles a data moat will play for companies. This could mean creating experiences that make the organization irreplaceable in the eyes of customers, as well as driving high-quality analysis and empowering teams from marketing and sales to design and development. Keep reading to see where your company fits in or connect with us for a complimentary consultation.

Robert Balaban is a Senior Data Engineer at Transcenda. With a strong focus on data pipeline design, optimization and data-driven decision-making, Robert’s focus is transforming raw information into actionable insights.

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