Data Traps and Treasure Hunts

by Simone Steel, Chief Data Officer at Nationwide Building Society

The role of data in supporting business strategy is unquestionable, but internal organisation tensions still exist between business and technology regarding data management and stewardship.

Over the last few decades, large, traditional financial service organisations have embraced the reality that they are software dependent. Some even managed to catch up in their digital channels to customers. Most still have stacks of legacy systems and practices that, at best, struggle to imitate the sort of agility needed to cope with fast change safely and sustainably. It took twenty years for the idea that “every business is a software business” to take hold, At the ever-accelerating pace of technological innovation, some business will not have another twenty years to adapt to the shift from the compute-intensive to the data-intensive era. The role of Chief Data (and Analytics) Officer, CDO, must quickly evolve and become more impactful and effective in helping businesses stay relevant.

In facing this reality, I’m sharing some insights from my own experience to help the CDO community to avoid some traps (anti-patterns) and to adopt behaviours (patterns) that are likely to yield better results.

Anti-pattern – Data strategy through slogans

The CDO role demands clear communication about how data supports business operations and strategic business goals. Here lies the first trap: generic statements like “Data is the new oil” or “managing Data as an asset” are masking the real complexities that Executives must understand. Leaders can no longer treat data strategy as a black box – this puts the business at risk.

Anti-pattern – Data issues magnet

Another common anti-pattern is the ease of assigning accountability for data to the CDO: from data privacy at the point-of-sale to inconsistencies between decades of overlapping management reports – it is convenient to bring all manifestations of data malpractice to a single accountable executive.

Anti-pattern – Square peg, round hole

Finally, the emerging data management disciplines pose a different sort of trap: what skills are needed to take the business into a data-driven era? SMEs in one industry or in internal systems, processes and products are no longer able to take the data management practice forward without developing expertise in external data dynamics. In fact, the internal-external data debate is no longer valid in an era of complex supply chains that operate on data exchanges. The new data professionals may be specialists in some techniques or fields, but also polyglots that learn data dynamics from a broader ecosystem. At the same time, jobs that evolved to for one purpose need to co-exist and collaborate with emerging jobs. A notable example is IT Architecture and Governance roles, which define and control development of deterministic software, but cannot be directly transposed to the delivery of Data Science products.

Pattern – The right questions

How can those traps be avoided?

A starting point is helping the Executive team get on the same page: what are the treasures that your organisation is seeking to find through data? As seen in the anti-pattern, simply stating “getting more value from data” is not sufficient. Is it data to optimise production processes and stay competitive? Is it data to understand current customers’ needs and shape new services? Is it simply to improve the quality of the outcomes to stakeholders, such as regulators?

Without the shared perspective of value, the CDO will inevitably come short of expectations.

Pattern – X-ray

Another helpful behaviour is to harvest (often unused) data about how the business really works and develop a language that is helpful to the executive team. How much business activity is happening throughout the virtual production line? Most automated and semi-automated processes leave a trail of breadcrumbs (metadata) that can indicate volume and timing of activity. When analysed and visualised, the CDO can make valuable contributions to optimisation decisions, especially around costs and controls. The CDO can move away from the anti-pattern of “target for data issues” and become a valuable partner.

Pattern – Fit for purpose

Leadership in the data-driven era requires broad understanding of the role of data in the business anchored on simple language, not jargon. Every conversation is an opportunity to engage on basic principles and challenge some norms. For instance, do employees know or have the means to know when they are creating erroneous data? Do they know what the data is used for and the consequences of incorrect, inaccurate, incomplete, or missing data? Do leaders know the ratio of investment and operational expenses going into data workarounds and remediation? This requires a willingness to learn at all levels of the organisation, beyond the groups that self-selected into data professions, such as data governance, database administration, data science. Data literacy and data culture are terms that are too vague to convey the importance of large-scale adoption of tangible and clear principles and rules.

I hope these anti-patterns and patterns are helpful in shaping the future of data in your organisation. In practice, they help me create a broader coalition of executives that see data as complementary to the business strategy. Demystifying the language around data issues, improving access to data, and creating visibility and control of data flows are some of the ways I am putting these insights into practice. I would welcome learning from your own experience in navigating this emerging field of knowledge.

Simone Steel, Chief Data Officer at Nationwide Building Society