The seven characteristics of the data-driven enterprise

Published on the 21/02/2024 | Written by Heather Wright

The seven characteristics of the data-driven enterprise

McKinsey outlines how to get to data-driven nirvana…

McKinsey is getting bolshy about the data-driven enterprise.

In a new report, it says by 2025 – just 10 months away – most employees will be using data to optimise nearly every aspect of their work. Going further, it says smart workflows and seamless interactions among humans and machines will likely be as standard as the corporate balance sheet.

“Data marketplaces ultimately empower companies to build truly unique and proprietary data products and gain insights from them.”

The strategy and management consulting firm has long pushed the data-driven enterprise concept – one that, to be fair, has been well embraced by organisations as they seek to harness data across the business to gain insights and drive competitive advantage.

But as organisations continue to grapple with the challenges of data – from dealing with the never-ending sprawl and data silos, to data governance and modernising architecture – McKinsey sees big opportunities for those organisations who exhibit the right characteristics outlined in its The Data-driven Enterprise of 2025 report.

Significant tailwinds, including rapidly maturing technologies, favour data driven enterprises and more recent disruptions and recessions highlight that companies who invest in innovation as part of day to day business have weathered the storms better. Add to those too, the AI push, and its underlying data needs.

McKinsey says data and analytics represent a 20 percent growth opportunity, but to harness its full potential, organisations must become truly data-driven, embedding it in every decision, interaction and process.

But how do companies become this mythical ‘data-driven enterprise’?

According to report, seven characteristics will define the data-driven enterprise, with many companies are already showing at least some of those characteristics.

Unsurprisingly, data being embedded in every decision, interaction and process is the first characteristic, with the report noting that data driven approaches currently are often sporadically applied across an organisation.

That’s where nearly all employees ‘naturally and regularly’ leveraging data to support their work comes in. Come 2025, the report says rather than defaulting to solving problems by developing extended roadmaps, employees will look to use data techniques to solve issues quickly.

Automation of basic day-to-day activities will free up employees to focus innovation, collaboration, communication and other more ‘human’ domains, and a data-driven culture will foster continuous performance improvement, providing ‘truly differentiated customer and employee experiences’.

It cites the example of store managers providing a differentiated shopping experience using real-time analytics to identify and then direct loyalty-program customers to products as they shop, and streamlining or completely automating checkouts.

But in order to achieve that state, McKinsey says companies will need a vision and data strategy which highlights and prioritises transformational use cases, along with the technology – think cloud-based infrastructure, real-time analytics and flexible database/data-model tooling to support querying of unstructured data.

There’s also the human element, with the need for data literacy and that oft-touted data-driven culture.

Organisations will also need to be able to process and deliver data in real time – that’s the second characteristic outlined in the report.

For many, that’s a key challenge today. It’s a case of ‘data, data, everywhere…’ but only a fraction of data is ingested, processed, queried and analysed in real time thanks to tech challenges and the computational demands of real-time processing.

Come 2025, McKinsey says we’ll have vast networks of connected devices gathering and transmitting data and insights, often in real time. Offerings such as Kappa and Lambda, enabling near-instant insights to data, sophisticated advanced analytics, more powerful edge-computing devices enabling processing at the source and advanced connectivity will all play a part.

The issue of data everywhere rears its head again in the third characteristic of data-driven enterprises: Flexible data stores which enable integrated ready-to-use data.

Relational database tools will give way by 2025 to different offerings including time-series, graph and NoSQL databases to enable more flexible ways of organising – and querying – data.

Having a data operating model which treats data like a product, with owners for all data, is the fourth characteristic, requiring businesses to understand their data sources and types for all data, and have operating models which establish owners for all data ‘products’.

Dedicated teams at retail companies developing data products such as ‘product 360’ and ensuring the data asset continues to evolve to meet the needs of critical use cases is one ‘everyday application’, while for healthcare organisations may stand up product teams to develop, maintain and evolve ‘patient 360’ data product to improve health outcomes.

For organisations winning at being a data driven organisation, there’s change too for the chief data officer, who, along with their teams, must must expand from being seen as a cost centre responsible for compliance to generating value.

If you’re not already on that road, the report says getting started will mean having conversations with business-unit leaders to identify opportunities for leveraging data to drive business value, developing holistic priorities and reinforcing the ethical use of data.

While earlier characteristics dispelled siloed data within the organisation, McKinsey says another key characteristic of data-driven enterprises will be greater data-sharing arrangements with external partners and even competitors – something currently still ‘uncommon and often limited’.

In fact, McKinsey says data-ecosystem memberships, facilitated by common data models and data alliances and sharing agreements, will be the norm, with companies pooling data to create value that is much greater than the sum of its parts, providing valuable insights for all members.

“Data marketplaces enable the exchange, sharing and supplementation of data, ultimately empowering companies to build truly unique and proprietary data products and gain insights from them.”

It’s a world where manufacturers share data with partners and peers through open manufacturing platforms to provide holistic views of worldwide supply chains, pharmaceutical and healthcare organisations pool data and financial services organisations harness data exchanges to create new capabilities.

Rounding out the seven characteristics is that data management is prioritised and automated for privacy, security and resiliency.

Today’s view of data security and privacy as compliance issues will give way the mindset that data privacy, ethics and security are areas of required competency, driven by evolving regulations. Self-service provisioning portal will manage and automate data provisioning using predefined -scripts’ to safely and securely provide users with access to data in near real time, improving productivity, and automated near-constant backups will ensure data resiliency with faster recovery procedures providing rapid recovery if needed.

“Rapidly accelerating technology advances, the recognised value of data and increasing data literacy are changing what it means to be ‘data driven’,” McKinsey says.

“Those able to make the most progress fastest, stand to capture the highest value from data-supported capabilities.”

Post a comment or question...

Your email address will not be published.

This site uses Akismet to reduce spam. Learn how your comment data is processed.


Thank you! Your subscription has been confirmed. You'll hear from us soon.
Follow iStart to keep up to date with the latest news and views...