In today’s data-saturated world, adopting a data centric mindset proves crucial for remaining competitive. Indeed, it is data that gives businesses insights and enables good decision-making. What’s more, data now transcends its role as a mere by-product of software applications, emerging as your most precious business asset. Further, businesses must realize that software and business methodologies will come and go, while data will remain a constant and a permanent resource. In this article, I’ll look into the challenges associated with handling data overload and the risks of focusing solely on a software-centric approach. Moreover, I’ll introduce you to an executive-level checklist that will help you get your business started on its data-centric transition.

“We are surrounded by data, but starved for insights.”

Jay Baer

1. Businesses Crave Insights, Yet Struggle with Data, Software, Tech, and Hype.

Within the data-intensive landscape of modern businesses, we see both large and small companies face increasingly larger data sets. However, harnessing the power of this data to gain critical insights proves daunting for most. This is because there is so much data, monolithic software, emerging tech, and hype for businesses to fathom. Indeed, this confusion only exacerbates the challenge of remaining competitive. Moreover, businesses are increasingly frustrated by their inability to stay informed in a world with an ever-growing wealth of data essential for success. Let’s look further at these issues.

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a. Business Data Overload Produces Few Insights.

First, this data ordeal results in extreme hardship for businesses to even glean any actual insights from their data. In particular, business analysis becomes a mind-numbing experience. Indeed, businesses routinely sift through vast amounts of irrelevant data that is incomplete, inaccurate, or outdated.

“People spend 60% to 80% of their time trying to find data. It’s a huge productivity loss.”

Dan Vesset

b. Is There a Real Technological Solution to Business Data Overload or Is It Mainly Hype?

Without a doubt, there is a lot of hype, but there are also a lot of new data-centric technologies. For instance, only a few decades ago, businesses had only to contend with a handful of data-related terms and concepts. At first, technology gurus called this new data phenomenon  “big data”. Then, all businesses had to do was store it in “data warehouses”. Now as more and more date idioms increase in number. we ask which one is the right solution? Is it “data-driven”, “data mesh”, “knowledge management”, “data silos”, Single Source Of Truth (SSOT), “digital twin”, “data lake”, “knowledge graphs”, “data fabric”, “metadata”, “data oriented design (DOD)” or something else?

Indeed, it is challenging to determine what new data-related concepts are hype and which are not. In many cases, the concept is valid, but it often gets oversold and misconstrued by an over-zealous tech sales team. Worse, a business will buy into the new, shiny tech solution without doing the due diligence. Positively, business leaders need to understand the technology and figure out if it really fits their business requirements.

“Executive management is more likely to invest in data initiatives when they understand the ‘why.’”

Della Shea

2. Is Our App-Centric Mindset Preventing Us From Getting The Data Insights We Need?

Without a doubt, software has transformed our business landscape, but we must now ask ourselves whether it may be part of the problem in today’s era of “Big Data”. Traditionally, we have used software to process data as an input or as an output. Indeed with most traditional software, data is not the central focus, it is a by-product. As the years have gone by, this practice persists with the advent of enterprise software and Software as a Service (SaaS) platforms. Over time, businesses have integrated these systems with other systems, yet these platforms still often regard data as a by-product.

As a result, many businesses now have aging software data silos. To confront this issue, businesses have turned to data integration and Business Intelligence (BI) tools to unify these scattered data sources. However, this often seems like a patchwork fix rather than a strategic move. So, let’s look further into what is going on with business software and is it time to stop being application-centric.

a. Exploring the Impact of Monolithic Applications and Emerging Technologies on Business Data Dysfunction.

You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric

Many businesses have become overly application-centric, which prevents them from gaining real insights from their valuable data. This issue arises because many companies rely on numerous monolithic software applications that generate vast amounts of data. For instance, many supply chain managers routinely work with several systems such as ERP, TMS, WMS, OMS, CRM, Procurement, SCM, Invoicing, Accounting, SCP, and more.

Worse, rapidly emerging technologies like Internet of Things (IoT) devices are generating massive amounts of new data. Additionally, other technologies like AI require large, high-quality data sets to function effectively. However, the data needed for AI is frequently confined within these software silos, making it fragmented, inaccurate, and duplicated. For more discussion on the dangers of having an application-centric mindset, see my article, You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric.

Now, there is hope for getting out of this data nightmare. For example, some software developers have started to take a “data-oriented” approach to developing software to address the advent of “big data”. This software development approach is radically different. However, it is a challenge to implement without business buy-in to this data-centric approach. 

b. What If Businesses Started Putting Their Data First Over Their Software Applications?

So, first and foremost, businesses should adopt a “data-centric” mindset. This is a crucial initial step for gaining valuable insights from their data and enhancing competitiveness. Indeed, they need to think of their data as a product, not a by-product, and view it as a tangible, permanent asset. In contrast, they should see their software as temporary, since it changes over time. Embracing this mindset will set businesses on the path to obtaining meaningful data insights.

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3. So What Does Data Centric Mean And How Can Businesses Get Started?

To get started with understanding exactly what “data centric” is, we need a definition and also what it is not. For instance, “data centric” is not “data driven”. In many cases, people have overused this term where it has become an ambiguous “buzzword”. Also, data centric does not mean that businesses need to put all their data in one database or software application. For many businesses, it would take years to consolidate all their data into one application, and by then, the software would probably be obsolete.

a. What Exactly is Data-Centric?

However, a business can start having a “data centric” mindset today, and soon the automation will follow. Here is a definition for data centric.

Data Centric Definition

A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation

“Data centric refers to an architecture where data is the primary and permanent asset, and applications come and go.  In the data centric architecture, the data model precedes the implementation of any given application and will be around and valid long after it is gone.”

TDAN, The Data-Centric Revolution: Data-Centric vs. Data-Driven

I like this definition. It defines data as the primary component of business technology. Specifically, this definition tells us that technology, software applications, and automation will come and go, but our data will never grow obsolete. Indeed, data is a permanent business asset that businesses do not need to constrain within any particular technology or software application. That’s it. By adopting a “data centric” mindsets, businesses will remain agile, have one truth, keep things simple, and they can continue to innovate. Moreover, data silos, information duplication, and data inaccuracies will fade away.  For more details on the advantages of a data centric business, see my article, A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation.

b. How Can Businesses Get Started?

So, how can executives get started to transform their organization into a data-centric business? Well, one way is to use a Data-Centric Business Strategy Checklist that I developed. This checklist is designed to help executives with leading their organization’s shift to a data-centric business. Specifically in this checklist, I’ll detail the critical executive-level tasks required for success. This includes establishing enterprise-wide data-centric guidelines for IT projects and driving consensus on key business terminology. Bottom line, this checklist provides a pathway to success for executives to better leverage their organization’s most important asset, their data. For details, see my article, A Data-Centric Business Strategy Checklist: The Way To Energize A Digital Enterprise To Be More Agile, Bold, And Simplified.

A Data-Centric Business Strategy Checklist: The Way To Energize A Digital Enterprise To Be More Agile, Bold, And Simplified

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