Data Agility: It's Time for Chief Data Officers to Realise They're in the Marketing Department Too

Whilst 'big data', 'GDPR', and 'personalisation' are now part of the common lexicon, a significant proportion of companies are still hesitant to adopt agile processes when it comes to managing their data. As Margaret Wagner (pictured below), EVP chief growth officer at Merkle EMEA, writes – companies should think 'data agility', and not merely be content with expanding their data assets without leveraging them for the benefit of both the business and the consumer.

A recent Gartner study looking at the growing role of the chief data officer revealed that no matter what companies invested in data analytics, it was culture that had the biggest impact on business success. Over a third (39%) of the survey’s respondents identified cultural resistance to change as the main obstacle for data analytics success.

That’s because there are very few company cultures which reflect the simple fact that, when it comes to data, everyone’s in marketing. At a time when expectations of brands are at an all-time high, adopting a people-based marketing (PBM) approach has never been more urgent. By enabling marketers to speak to specific people, instead of fuzzy proxies, people-based marketing helps brands serve relevant information to customers wherever they appear in the marketing ecosystem. In turn, this fosters personal, long-term relationships with lifetime value baked in.

When customer expectations move as quickly as the latest iOS update, prioritising data and analytics should be embedded into the organisation’s culture, not siloed within a single department. For businesses and marketers who want to keep up, and get to customer-centricity by driving deeper and more meaningful engagement, the name of the game is Agility – but not as you know it.

Margaret Wagner, EVP, Chief Growth Officer, Merkle EMEA

By adopting a data-first approach, all the way from the chief data officer, to legal, to customer service, an organisation can become much more ‘agile’ with the data they have, instead of simply looking to expand their assets and hoping for success.

Three steps to improve data agility

There are three important steps organisations can take in their journey towards Data Agility:

1. Accessibility

The first is accessibility; many companies are already in the process of making the right data accessible, and collating disparate datasets across the organisation into one central location. Whilst this is absolutely a step in the right direction, the process can take between 3-5 years to complete, depending on whether you are first-party data rich in the first instance. There is, of course, a question of first mover advantage here – the first with the ball is more likely to score – but while everyone is focused on laying the perfect foundations, time is ticking by. Organisations should focus on making the most of the data assets they have, instead of waiting for perfection and disappointing customers in the short term.

2. Insight

The second way to think about data is insight – something that is actionable for companies no matter where they are in their journey towards accessibility. Finding insight requires drawing assumptions based on the data you already have, which you can then use to build both a picture of the known customer, but also extrapolate to reach other potential customers at a time that is relevant and adds value to their lives.

3. Unified approach

Most importantly, Data Agility should be considered a team sport – it doesn’t matter whether you’re a data scientist or in legal, you’re all in ‘marketing’ when it comes to the customer. Indeed, a company is only as Data Agile as its slowest department. Indeed, if your digital team operates at the speed of light, but there’s customer insight languishing for days in legal, you’re not Data Agile.

Leverage your data

Most companies already have a substantial amount of data at their fingertips; and every day spent not leveraging it is valuable time wasted. It’s no use leaning on rudimentary personalisation to tide customers over in the meantime either. Whereas effective data mining used to mean knowing where the customer was due to appear in the buying cycle, today’s consumer requires much more from a brand than just knowing when the best time to sell is.

Instead, brands today must earn their customers’ loyalty by understanding where their product fits into their hierarchy of needs at any given moment, and interacting with them accordingly. Data Agility makes this happen, but it requires taking what you have today and making it work for you – quickly! Whether you start with content, tech, or creative, only data will drive the actions required to impress today’s consumer.

Embrace GDPR without fear

However, in today’s GDPR world, chief data officers often feel that their role is simply to ensure data is compliant. While this is, of course, critically important, it should not be at the expense of creating long-lasting relationships with your customers. Indeed, protecting customer data is everyone’s number one priority, but being too fearful to action customer data, when compliant, could be costly to businesses.

Why data agility is important

Although we’re seeing an increase in the number of chief data officers, it’s more important than ever that organisations know how to make the most of their investments by placing greater value on their data assets. By deploying a Data Agile approach, organisations will shift their focus on operational agility and transformational outcomes, to drive out ever greater value from resources and build a deeper engagement with customers and subsequently, achieve sustained success.