Why It's Finally Time to Become a Data-Driven Enterprise — and Why It's So Hard
Why It's Finally Time to Become a Data-Driven Enterprise — and Why It's So Hard
Most enterprises still struggle with deploying and leveraging effective data infrastructure. But generative AI and other recent developments are causing enterprise IT leaders to finally pay attention.
The drumbeat to become a data-driven enterprise has been beating for so long that it's become background noise for most enterprise IT leaders. But as generative AI has captivated enterprise executives, many IT leaders are realizing that they need to do more to build and manage a data infrastructure that can support their organization’s future data-driven ambitions.
I recently took on a fractional role as Chief Strategist with a company called Waterloo Data, and as I have really dug into this space I’ve become acutely aware of the challenges facing most enterprise IT leaders.
Waterloo specializes in helping enterprises leverage data to build models and create powerful competitive advantage via their data. It leverages a holistic end-to-end approach that goes beyond the one-dimensional, technology-centric focus that hinders most data efforts to create genuine data leverage.
But it can seldom start there.
In case after case, it finds that most enterprises lack a solid data foundation — core infrastructure, secure data pipelines, dynamic data integration strategies, data management capabilities — that are necessary to power the advantage-driving data strategies that business executives are seeking.
As a result, Waterloo spends most of its time doing blocking and tackling to help organizations lay that foundation. The reason is simple:
Laying a proper data foundation is a lot harder than it appears.
The Business Imperative for Laying the Right Data Foundation — and Why It’s So Tough
It may be tempting to gloss over this latest generative AI-driven focus on data. After all, we’ve all lived through these hype cycles before.
But regardless of how generative AI plays out, the criticality of data to the future of the enterprise should not be underestimated.
As a recent CIO.com article makes clear, it is a definitive executive mandate:
It’s no surprise that becoming a data-driven company is at the top of the corporate agenda. A recent IDC whitepaper found that data-savvy companies reported a threefold increase in revenue improvement, almost tripling the likelihood of reduced time to market for new products and services, and more than doubling the probability of enhanced customer satisfaction, profits, and operational efficiency.
Yet, most organizations still struggle with building both the cultural and technological foundations necessary to become truly data-drive. The article continues:
But according to a January survey of data and information executives from NewVantage Partners, merely a quarter of companies describe themselves as data-driven, and only 21% say they have a data culture in their organizations.
The article goes on to identify that the real issue isn’t technology, per se, but rather the “softer” issues such as:
Linking underlying data to business value
Creating a data-centric organizational culture
Data quality and data lineage, which drive trust in data
Dealing with data ownership issues (linked to trust and culture)
The team at Waterloo has found all of these to be true. The issues are rarely driven by the lack of technology as much as an understanding of how to bring together the various stakeholders and break through the cultural challenges to then architect a data foundation that simultaneously meets everyone’s needs and delivers the business value the organization needs.
It really comes down to taking an end-to-end approach — which may be the hardest part of the entire process.
Recent Signals of a New, Holistic End-to-End Era of Data Foundations
Waterloo is not alone in recognizing these challenges.
At Build, Microsoft’s recent developer conference, the company announced a new solution called Fabric. Dubbed “data analytics for the era of AI,” the company recognized the complex challenge of building these integrated data foundations and echoed the need for an end-to-end approach:
Powering organization-specific AI experiences requires a constant supply of clean data from a well-managed and highly integrated analytics system. But most organizations’ analytics systems are a labyrinth of specialized and disconnected services.
And it’s no wonder given the massively fragmented data and AI technology market with hundreds of vendors and thousands of services. Customers must stitch together a complex set of disconnected services from multiple vendors themselves and incur the costs and burdens of making these services function together.
Today we are unveiling Microsoft Fabric—an end-to-end, unified analytics platform that brings together all the data and analytics tools that organizations need.
While the company is dealing with only the technology aspect of building a data foundation, implicit in its message is that by creating a single, unified approach to data infrastructure, it can help cultivate the data-driven culture that must come with it.
In a similar vein, Digibee’s recent announcement that it received a $60MM Series B investment (quite a feat in this capital market) is another sign of this end-to-end holistic trend as the company’s primary driver is the democratization of integration capabilities so that they can be embedded in end-to-end development practices.
It’s Time to Join the Data-Driven Ranks
I get that being an enterprise IT leader today is a study in balancing competing priorities.
You are under overwhelming pressure to somehow do it all: deliver bullet-proof reliability, neverendingly reduce costs, continously adapt to changing market conditions and customer demands, and drive innovation.
Easy, peasy, right?
It’s no wonder that it’s hard to prioritize the transformation into a data-driven culture, do the heavy lifting of setting a tightly interwoven data foundation, and help lead your organization to become a data-driven enterprise. But it’s becoming abundantly clear that this transition is the macro trend that will ultimately drive the entire enterprise agenda.
As an enterprise IT leader, you need to be leading the charge.