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Change tends to come in two flavours: gradual, and sudden. Looking one year on from the start of global pandemic, both are equally applicable to the force of change we’ve experienced. For those of us who’ve been in the IT industry for many years, the data economy that has become increasingly evident has materialised from the gradual development of the technology, processes and human skills needed to operate a data-driven business at scale. Yet, it took the sudden outbreak of the pandemic to catalyse change and put digital transformation right at the top of every organisation’s agenda.

As we see companies react at unprecedented speed to make sure they have the IT capabilities they’ll need to compete in this new data economy, it’s easy to lose sight of what really underpins the value of technology: human skills and ingenuity. It’s this blend of human and machine capabilities, and the synergies between them, that manifests in sustaining what makes your business unique in its field or sector – your company DNA.

Your company’s DNA reflects your people, your overall business, and the technologies you have in place. It’s like a code that determines the outcomes you can expect from your business and human capital. Recognising what makes your business distinct and leveraging these qualities gives shape and direction to how you innovate and grow.

As a business leader you can help cultivate and direct your company’s DNA. Doing so requires focus on your people, your data, and how these two forces inter-relate. I’d like to highlight five key priorities that can help unlock the code to your company’s DNA and support in finding the optimum balance between being data-centric and human-centric, all with the goal of protecting what makes your organisation unique.

5 priorities for enhancing your company’s DNA:

  • Support data literacy and the development of both hard and soft skills

There are few roles within any organisation that wouldn’t benefit from some degree of ‘hard’ data skills. Almost every function now requires at least a basic ability to analyse, measure, visualise or comprehend data in furthering a definable outcome. Business growth and corporate decision-making are examples of areas that increasingly rely on the persuasive impact of quantitative, data-driven arguments.

At the more technical end, however, skills such as data science, business intelligence and application development have long been, at least by perception, the preserve of those in specialised roles. It’s natural that some people will shy away from more technical tasks or deflect them towards those to whom the skills come more naturally.

In recent years, though, we’ve seen a marked change at both a hardware and software level, allowing non-data experts to work with data and artificial intelligence to integrate it with their everyday tasks. These technical capabilities need to be reinforced at a process level to enable and encourage a broad range of internal stakeholders, across back, middle, and front office, to onboard and participate in data initiatives.

  • Democratise data accessibility and usage across the organisation

Data is a collaborative endeavour, and no business can reap the value of its data without everyone playing their part. This applies across all stages of the data lifecycle, from identifying useful data sources, collecting data, and creating standards around format and quality, through to applying governance protocols, enabling accessibility, and embedding a data-led approach across business processes. The better your employees get at managing data, the more everyone benefits as the value and utility of data applications and processes compound over time, leading you towards the ultimate objective of becoming a data-driven organisation.

As a leader you should think carefully about how you can design systems and processes around your people to aid this democratisation. By putting people at the centre, you can help them extract valuable insights and make more informed decisions that lead them towards fulfilling their objectives. It’s important to gather user feedback and monitor user experience based on definable metrics, and then use this intelligence to guide whether the choice of technology and onboarding processes are in fact acting as an enabler for greater adoption.

  • Identify and counteract bias

Every technological advance creates a new set of considerations for decision makers that can make or break its success. The pervasive use of AI and data has highlighted risks that may otherwise have been overlooked; while the applications themselves may be neutral, both the data they’re ingesting and those using them may bring unexpected and potentially dangerous biases.

This is becoming a greater concern as bias can serve to undo the benefits of data and AI – rather than creating fairness it can serve to protect the status quo by placing too much value on past data. There have been countless news reports in recent years showing where data models have reinforced gender bias by, for example, serving job ads for nurses to females or prioritising males for CEO roles. This presents far more than just a reputational risk as it works against the objective of becoming a more diverse and inclusive organisation.

Rather than viewing this as an intractable challenge, you can seek solutions from the data itself. Counteracting the risk of bias begins with self-awareness of your organisation and the data it holds, which in turn helps to direct procedures to make sure you’re asking the right questions, actively checking for bias, adopting peer review processes and learning from past issues. This approach can then be reinforced with technological safeguards to help neutralise the risk of bias or alert users to cases where it might be present.

  • Drive innovation and find competitive advantage

One of the most valuable gifts that developments in AI and data applications have to offer is unlocking the human capacity for innovation. Conventionally, this capacity has had to be counterweighed with constraints on time, resource, and risk, meaning that opportunities for process enhancement, product improvements and the reimagining of business models have often not been properly explored.

In a data-driven environment, organisations have greater ability to model and predict at scale, giving employees more leeway to try new things. AI and data processes act as a self-reinforcing virtuous cycle, allowing employees to test new ideas and receive rapid feedback on whether the results are positive and the improvements viable. Such experimentation shouldn’t be an appendage to an employee’s job function, but actually a core part of their responsibilities.

To embed this in your workplace, start from the perspective of defining what your employees are best at – even irreplaceable at – and consider how data and AI can help them to do it better, faster, and more accurately. It’s important to emphasise to employees that trial and error is part of the job. There’s no such thing as ‘failure’ if experiments are made in a risk-controlled way, and learnings are gathered for ongoing improvement.

  • Implement data strategy from the top-down

While there is no single data strategy or approach that can applied across organisations of all different sizes and sectors, there’s one common characteristic among those that do it right: becoming a data-driven organisation starts at the top. From board level through to operations, finance, IT and all other departments, data must be fundamental to how the organisation works and how decisions are made.

As the business world adapts to global uncertainty, technology has the power to overcome the volatility and ambiguity, and help businesses stay connected with their customers, to innovate and to thrive. The source of this transformation is data and it’s time for businesses to become ‘data-centred’ and to capitalise on the growing data economy. In this new economy all businesses are data businesses, and every employee works in a data ecosystem. A data strategy, focusing on skills, literacy and analysis therefore needs to be put at the heart of your organisation to reap the value of transformative technologies while protecting what really drives competitive advantage – your people.

In this regard, people and technology need to meet in the middle as it’s at the intersection where skilled, enabled employees meet intelligent systems that magic is made.

Becoming ‘data-centred’

The evolutionary biologist Richard Dawkins once said that “DNA neither cares nor knows. DNA just is. And we dance to its music”. The elements that constitute your organisation’s DNA may not be obvious – from the data centre infrastructure and servers that manage your data through to the people that embrace it and turn it into business wins. Yet every working day these elements act like genetic instructions for the development, function, growth, and reproduction of your business operations. And it’s this subtle dance that separates you from every other organisation.

Maintaining healthy function requires, firstly, broad organisational consensus on what makes your company’s DNA unique – what can your organisation offer that no one else can, and what role does your data play in re-enforcing this advantage? Secondly, it’s vital to have executive sponsorship to make advancement in AI and data an organisation-wide priority and ensure that no one is left behind. Most importantly, your leaders need to be actively encouraging employees to level up on their data literacy, building a stable foundation of data self-reliability and responsibility across the business.

These aren’t short-term considerations; it needs a longer-term vision to operate in a ‘data-centred’ way. With human-centricity and data-centricity working together, the iterative changes and benefits may come gradually before they become apparent – suddenly.