1 – Surf the wave of hype
Back in 2011/12, big data erupted as a major area of organisational focus and hype, not least from technology vendors who stood to benefit directly. Data and analytics have since settled-in as critical new functions at the heart of leading companies, with the majority of firms adopting some form of these tools and assets.
So, it could be seen as hypocritical to resist other innovations which are now themselves benefitting from hype. Artificial intelligence (AI), robotics and applied science are undoubtedly at the peak of that curve, while an entire new sector – fintech – has emerged on the back of data and digital combining to address new regulatory requirements, such as Payment Services Directive 2 and Open Banking. With regard to the latter, one senior data practitioner in the banking sector noted that entitled consumers know what technology is available to companies and are demanding a better customer experience as a result.
It is impossible to fight against this hype cycle, but it can be harnessed to introduce foundational data projects which lack glamour, such as data quality, yet are fundamental components of those new programmes. One insurance provider noted that the desire to drive new products and services based on data science – itself a hyped activity several years ago – had allowed it to win investment into resolving long-term data problems, such as having seven different address management systems each operating to different standards and data models, meaning they failed to pass through integration filters being applied to build a new single customer view.
Hype is an energy that can galvanise an organisation into action – hitching a ride on the back of it to achieve core data capabilities is therefore a smart move.
2 – Find a champion
Top-level buy-in to data projects has long been recognised as critical to creating and sustaining data as a capability. In some cases, organisations are fortunate to have incoming chief executives who are data-literate, get its potential and push for enterprise-wide adoption of data-driven techniques and tools. Data being given voice from the very top of the business is the gold standard and often precedes the creation of a central data office and appointment of a chief data officer (a role that was the subject of hype in 2013/14, but is currently in a trough).
Other champions may also emerge, typically in the form of a chief technology officer (CTO) who leads a digital transformation. It is not always the case that the CTO is a natural data champion – this is more often the case for chief information officers (CIOs). But two members – one a charity, the other a professional information provider – reported a renewed focus on data on the back of CTO-driven projects.
There are risks in having a champion, too. One is the potential impact of their sudden departure, a risk that is highest among CEOs as this is a very political and exposed position. Another is that the champion turns out to be pursuing a personal agenda or goals that are not fully aligned to the business strategy and data strategy.
Finding a champion is therefore a valuable short-term way of driving data transformation. But decoupling from the champion and establishing a stable function with its own political power has to be the long-term objective.
3 – Create a data culture
Data literacy is a term currently enjoying its own moment of peak hype. As a concept, it is clearly worth supporting given its aim of increasing the level of understanding of data across organisations (and populations). The majority of employees in businesses will not have the level of skills (or potentially numeracy) found in data and analytics teams, constraining their ability to absorb and adopt the outputs from this function. Similarly, STEM-qualified staff will be in the minority outside of technical departments.
But data literacy is not the same thing as having a data culture. To be truly data-native, an organisation needs instinctively to look for data to support decisions and processes, think about data strategy when developing new services, have an automatic desire to put privacy at the heart of that data strategy, and to build-in data standards, collection, verification and sharing at every opportunity.
To stimulate this data culture, it may be necessary to inoculate the organisation from outside, perhaps through the use of third-party business partners and contractors to kick start the process. Building a data academy, either in-house or by working with DataIQ, offers a mid-term to long-term solution and keeps up the momentum of data transformations, especially in year two onwards. Even simple lunch-and-learn sessions can give the business a better understanding of what best practice looks like.
Data can struggle to tell its story with the same clarity and energy that digital transformations have, not least because it is more complex and longer term in its delivery. Using communication and stakeholder engagement to sustain the message about data’s value is therefore vital to bringing a new data culture to life.
Case study – Global equipment manufacturer
In July 2018, a global equipment manufacturer which employs over 30,000 staff worldwide created its first data function. With a team of just 82 practitioners, the data office quickly recognised that it would be challenging to get traction in an enterprise of this scale. To support its goals, it has therefore adopted a three-pronged strategy to build-out a data culture:
1 – “Inception” communications strategy: In the film “Inception”, a team of industrial espionage experts are employed to embed an idea (to sell the business) into a target’s subconscious so that they will believe they came up with the idea on their own. In a similar way, the data team is seeding internal message boards, in this case on the Yammer platform, with success stories and deliverables about data and analytics. The hope is that business managers and leaders will then formulate ideas and queries for the data team as if they have originated these for themselves.
2 – Changing how change happens: In a business with a culture of innovation and R&D, change is a constant. But often, these digital transformations have pursued new solutions and tools without a clear understanding of what benefit or impact they will deliver. The data team is looking to provide data-driven insights and evidence to support (or counter) the business case in these circumstances.
3 – Embedding data methodologies: Data needs to be at the very core of the business, so new methodologies need to be developed, distributed and adopted. To support this, a data charter has been drawn up which describes five principles by which the function operates. In a strong indication of the impact of these strategies, the fifth of these principles – relating to the ethical use of data – has now been adopted in the organisation’s principles of operation.
