In today’s data-driven world, organisations that harness the power of data and turn it into valuable insights gain a competitive edge. However, many enterprises struggle to unlock the full potential of their data assets, despite significant investments in analytics tools and platforms. The key to success lies in implementing a coherent data strategy.
By Rudie Vermaak, data services executive at new-age solutions and systems integrator, +OneX
More than ever, winning organisations are set apart by their ability to turn the deluge of data flowing into their businesses into real insights. Leveraging data can give your organisation an edge by enabling you to make better strategic and operational decisions, automate more of your processes, and gain insight into the trends that are driving your business. As artificial intelligence (AI) continues to mature, the importance of data in achieving a sustainable competitive advantage will grow exponentially.
Yet many enterprises are struggling to exploit the full value of their data assets, despite the amount of money they’re spending on analytics tools and data platforms. A survey of 10 000 business leaders across 10 countries found that only a minority are using their data to make strategic decisions about pricing, launching in new markets, determining climate targets, and determining diversity & inclusion policies. A third reported that they are unable to generate insights from their data and 30% said they have too much data. So, what’s going wrong for the majority?
One of the biggest mistakes that organisations are making is that they’re not putting in place a coherent data strategy — even though most C-suite executives would agree that data is a strategic resource. A global study conducted by YouGov found that only 13% of organisations said that data strategy is a key part of their corporate strategy. Without an overarching data strategy in place, data siloes proliferate and people aren’t empowered to use this valuable resource — leading to suboptimal results.
What exactly does it mean to have a data strategy?
At a high level, a data strategy is a long-term plan that defines the technology, processes, people, resources, governance and policies you need to maximise the value of your data assets. It will set out how you will gather, store, share and use data to meet your goals and achieve better business outcomes. Your data strategy may embrace the tools and technical processes you need to maximise the value of your data–but it’s not primarily about technology. It’s about aligning your data with your strategic objectives.
A data strategy is key to gaining and sustaining a competitive advantage in an increasingly data-driven landscape. Your data strategy will enable you to identify your key metrics, establish processes for data analysis, and set out use cases for analytics, data science and AI in your business. It’s essential for turning vast volumes of information into meaningful insights that help you make better and faster decisions. This, in turn, empowers you to harness insights for innovation, customer experience enhancements, and operational efficiency improvements.
Furthermore, a data strategy helps to foster a data-driven culture within your organisation. It creates a structure for deploying the training, tools, and incentives you need to cultivate a data-driven mindset throughout your business. It promotes data literacy, encourages data-driven decision-making, and empowers employees to use data in their day-to-day work. Well-defined data ownership and strategy, governance, and internal education are all essential for democratising data in your business.
What challenges should your data strategy address?
In the absence of a data strategy, we see a range of challenges cropping up for organisations as they try to tap into their data. One of the major obstacles to unlocking value from data is the existence of data siloes. With different departments and teams managing their data independently, data is scattered across multiple systems, effort is duplicated and there is no single view of the truth. It becomes difficult to analyse data holistically, limiting your ability to get comprehensive insights.
Without a data strategy, a company will probably not have standardised processes for collecting, storing and managing data. This can result in inconsistent data quality, with records that are inaccurate, duplicated or incomplete. In turn, this can lead to poorer business decisions and undermine organisational trust in the quality of the data. The lack of a roadmap may also result in inefficiencies in investing in data infrastructure, analytics tools, and talent. Ad hoc decision-making and wasted resources will inevitably lead to missed opportunities for innovation and advantage.
Finally, in today’s environment, data ethics, privacy and regulation are high on the agenda. Without a data strategy, companies often lack a framework for data governance, leading to challenges in data ownership, data stewardship, and data privacy. Inadequate data governance can result in compliance issues, data security vulnerabilities, and inefficient data management practices. This can expose your company to a range of legal, operational and reputational risks.
Steps to creating a data strategy
A data strategy is a ticket to play, no matter what the size of your organisation or in which industry sector it operates. A good place to start is by outlining the potential benefits of a data strategy for your organisation, which use cases it will support, and which teams and people need to be involved. Securing buy-in from a diverse set of stakeholders in leadership, the business and the IT team early in this process will vastly improve your prospects of success. Your data strategy team should have representation from all of these groups.
The next step might be to discover and catalogue the data you have in place, where it is to be found, how it is used today, and the quality and consistency of your data sources. Don’t restrict your process of discovery to internally owned data or structured databases — there might be useful insights to be found in unstructured data such as images, audio and video as well as in third-party data sources, ranging from public government databases and social media platforms to business partner systems.
From here, you can start to define your to-be state. This should include data governance and security standards, talent and training requirements, change management, and the technical infrastructure and tools you will need to bring your strategy to life. Although it is important to have a big-picture strategy, it’s also important to have some use cases that lend themselves to faster deployment. If you follow agile methodologies, you could map out your projects and aim to get some minimum viable products into production as soon as possible.
Conclusion
Like business strategy, data strategy needs to constantly evolve and be refined – it’s not a once-off programme or project. Data strategy is about recognising the strategic value of data and preparing for the future. Rather than sweeping away old technology and replacing it with new, a data strategy should help to transform the decision-making culture and how people interact with data.
Companies that get it right will extract more value from their data, benefitting from strategic advantages, and higher returns.