What does a future of integrated cross-functional data and less silos hold for the digital marketing analyst?

An increasing number of organisations are putting data at the heart of decision-making. According to a study by Dresner Advisory Services, 59% of organizations deploy big data analytics, up from 17% in 2015.

The business impact that comes along with an “Analytics First” data-driven culture is evident – with data-led organisations seeing an upward trend of 20% to 30% improvement in their EBITDA due to unlocking efficiencies and gaining new business insights.

As more data breaks free from silos and becomes progressively integrated across functional groups, a future where data is highly democratized will change the way many of us work.

How can digital marketing analysts better position themselves for this impending new reality?

We are already seeing marketing data getting further integrated with other business sources like sales, CRM, customer service, in-store operations, and supply chain management. There are opportunities for digital marketing analysts to provide insight into new trends and customer behaviours that can inform other functional groups outside of marketing.

To do this effectively, analysts need skills to frame questions based on a wider understanding of organizational goals and address them with actionable insights that can influence results in a meaningful way. There’s hence a greater need for hybrid roles that mixes both science and business acumen.

Proactively up-skilling not only in hard IT skills, but also in business domain knowledge and communication skills, will give a great edge for an analyst in finding data equivalencies from various business sources to derive interesting cross-functional patterns.

Communication and relationship skills are also necessary for analysts to be change agents in their own right in the progress towards a data-driven culture. Getting business managers to understand and trust data-led recommendations as well as breaking down organizational silos would benefit the analysts themselves to drive bigger scale and impact in the work that they do.     

What support should the industry provide to help them?

For the digital marketing analyst to succeed as best as possible in a data-led future, the foundation of an analytics culture needs to be embedded in organisations. This entails having business leaders to be trained as dedicated sponsors of data-driven cultures, maintained by a comprehensive data governance plan. Business leaders can reinforce such cultures by example – showcasing data behind the organisation’s decisions and results, leading to greater transparency. This in turn would encourage employees to trust and delve more into data. Employees themselves must be empowered to query, interact, review data and respond with timeliness.

Leaders can also do more with their institutional and retail shareholders. By highlighting the benefits of a data-driven culture to investors, this can stir up more confidence in capital investments that have to be made.  

Budgets should be set aside for data infrastructure and training not only for analysts but for employees in general. Organisation-wide training will ensure that there is data literacy across functions so that data can be truly accessible and reviewed.

Organisations could also add diversity within their analytics teams, which can be a mix between data scientists, data architects, statistical modelers and business analysts. Setting up a centre of excellence consisting of multi-disciplinary experts would do well to provide best practice, share success stories and conduct post-mortem learnings on failed projects. If companies choose to outsource, use analytics agencies meaningfully and ensure there’s a wide integration across the business. Avoid using them just to process data.

In most companies, up to 80% of an analyst time is spent simply finding, cleaning and organizing data, and the remaining 20% spent on actual data analysis. Proper data governance and processes, as well as adoption of cloud-based platforms and machine learning can help clear up time for menial tasks and allow analysts more time to really deep-dive.

Companies should also look into incentive schemes that reward those who proactively reach out beyond silos, integrate analytics, and gain new insights to solve everyday cross-functional business challenges.

With greater access and integration, there's a greater likelihood to be overwhelmed by data. Simplicity in approach is key. Don’t analyse everything. Analysts in an open-data environment should focus just on data that will help achieve specific business goals.

Who else could help?

Outside of the company sphere, industry bodies, educational institutions and governments can also do more to help organisations with their up-skilling needs. Just as how the Singapore Government and the IAB SEA+India have collaborated to form the Adapt and Grow Professional Conversion Programme (PCP) for Programmatic Advertising training for example, a specialized training programme can be etched out for analytics professionals to develop a better sense of business management and communications so that they be “translators” who understand the analytics and speak the language of business. Mentorship schemes could also provide a platform for analysts to gain such learnings from business leaders in situ.  

This piece was written by IAB Southeast Asia and India (IAB SEA+India) Analytics Committee Member Haikal Mohamed, Senior Manager, Digital Marketing, Southeast Asia, The Walt Disney Company.