Why businesses should strive to be data custodians, not owners, and the steps they can take to get there. 

There’s little argument that data is a hugely valuable commodity for businesses and perhaps the single most valuable commodity in today’s market. Indeed, some of the world’s biggest companies, like Facebook and Google, are built on the billions of dollars in profit that having and selling this data creates. 

This model has rubbed off on consumer-facing companies and created a mentality of ownership towards customer data — that it is somehow theirs to be exploited and profited from. However, this is a dangerous mentality. Not only can it lead to issues with privacy, security, and compliance, but crucially, it chips away at customer confidence. Consumers are becoming increasingly aware of the value in their data too, and intrusive marketing with their data at the root of it will raise suspicions as to whether their data is in safe hands. 

Changing Mindsets

Companies need to change their mindset and move away from the idea that they are the “owner” of their customers’ data. Instead, they need to take the approach of being a data custodian instead. Not only that, but they need to make their customers feel sure their data is safe too, and that it will only be used in the ways that they have explicitly consented to. 

This is only achievable with a comprehensive data strategy in place. Data strategy is imperative for democratizing data and building a strong culture where every employee thinks about data as a strategic asset — but also one that needs proper care and handling. That’s getting more difficult to ensure without a strategy in place. Companies now hold an overwhelming amount of data on their customers. Without a good understanding of where that is held and what they can do with it, ensuring privacy, security and compliance is much more difficult. 

The impact of data fragmentation

That’s because data sprawl is rife. In our post-COVID world, with digital transformation initiatives in full swing, many companies have data scattered between legacy on-premises systems and multi-cloud environments. That resulted in the fact that only 38% of respondents to a recent survey strongly agreed that they knew where all of their customer data is stored. Such data fragmentation doesn’t just raise security and compliance issues but also leads to a disjointed customer experience. Without individual customer profiles to store all a customer’s data in a single place, the opportunity to upsell or cross-sell with the data at a company’s disposal may be missed — or worse, wrongly targeted. Once again, this leaves customers questioning how safe their data is, and causes frustrations in the user experience to boot. This is why tactical and responsible custodianship of customer data is the goal and can make all the difference between a business retaining its reputation and sales volume and losing its customers’ trust and business. 

Underpinning a culture of custodianship with strong data strategy

For too long, compliance has been seen as a must-do cost center rather than a value driver. When organizations shift to a mindset of custodianship, compliance becomes a result of good data practices rather than simply a reason to do it. Developing a clear framework for how data is collected, stored, and used across the enterprise will help businesses leverage data assets, mitigate risks and increase customer trust. 

For any business assessing its data readiness and maturity, these are the key considerations when building out a data strategy: 

1) Set out your vision and business case 

The vision defines the broad strategic objective for building a data strategy, while the business case articulates the specific business opportunity. A vision statement should be broad, but actionable within 3-5 years. For example, “create a better customer experience by reducing the time it takes to resolve issues, delivering relevant marketing materials, and protecting sensitive customer data,” is a solid data vision. The business case must also be actionable but will be more pragmatic and hands-on, specifying the actual people, roles, technologies, and processes involved in moving your data initiatives forward. 

2) Appoint data champions to lead the way 

In recognizing that customers are always the owner of their personal data, organizations must protect data by ensuring that it can only be viewed by those with authority and consent to do so. This means outlining clear owners and processes within the data strategy that encourages the use of data without restricting it. The Chief Data Officer role has evolved over recent years from one focused on locking down and securing data to a business partner who stewards data in a way that it’s safe, trusted, and available to the business for drive innovation and value. 

3) Nurture a culture of custodianship 

A good data strategy spans the full business, avoiding departmental silos. Just as each business has different aims for its data initiatives, the framework guiding the culture will vary too. However, with a culture of custodianship, the proper use of data is encouraged, and tools made available to do so in a way that brings teams and data together to drive value for the customer and the business. 

This means moving away from being purely defensive, with an approach of locking data up and restricting access and instead instilling practices and providing tools to leverage data in a more collaborative way. 

4) Choose the right technology 

There are myriad data tools available today. When selecting the technology that will support their data strategy, organizations should consider platforms that enable them to bring data and teams together. Democratizing the use of data in this way, surfaces data across the business in a safe and trusted way, with users in different teams viewing the same data but with a different lens in line with their use case. In the context of data governance, “technology” primarily means automation. Many technology solutions and platforms exist to help automate different aspects of data governance, traditionally completed manually, and finding the right one is key.

For example, AI is able to automatically identify customer data at risk, allowing the organization to take action and ensure proper handling of that information and staying true to the notion of custodianship. With data initiatives always evolving, it’s important to choose a platform that delivers value today but can also adapt and evolve as requirements change. For this reason, focus on a platform that delivers flexibility and interoperability, and consider cloud-based tech for easy scalability.

Also, be sure to put intelligent automation at the forefront of considerations — this will help you get started quickly without massive and costly custom integration efforts. The importance of a well-run and managed data strategy cannot be over-emphasized when it comes to the correct handling of customer data. By combining the right people, processes and tools, a business — and moreover, its customers — can be sure that any data driving its initiatives is trustworthy, high-quality, available, and accessible to only those who need it.