In today’s business world, being technologically savvy is a must for most business managers. For example, supply chain managers are no strangers to enterprise software applications like ERP, TMS, and WMS, and they’re quite skilled with office productivity tools like MS Excel. Moreover, these managers know the value of data analytics and Business Intelligence (BI), and they can use them to guide important decisions. However, being data centric is something completely different. It means treating your data as an asset rather than as a by-product of your enterprise systems. 

In this data-rich world, a data centric mindset is critical to staying competitive. Data is no longer just a component of software applications, it is your most valuable business asset. It’s time for businesses to recognize that software and business methodologies come and go, but the data will always be there. In this article, I’ll take a closer look at the challenges of dealing with data overload, the pitfalls of being software-centric. Additionally, I’ll introduce you to the concept of running a data-centric business.

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

Jay Baer

Businesses Are Starved For Insights, But Continue To Grapple With Data And Data Technology Hype.

Let’s begin by examining the current data landscape for businesses. In today’s fast-paced environment, businesses are progressively dealing with larger data sets. However, many struggle to effectively utilize this data. This is because they find it difficult to navigate through the hype surrounding data technology to discover tangible solutions. Indeed, this complexity and uncertainty pose significant challenges. Amplifying this issue is the realization that businesses require an ever-growing amount of data to make informed decisions and maintain their competitive edge.

Hence, 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. Now, businesses routinely sift through vast amounts of irrelevant data that is incomplete, inaccurate, or outdated.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

Another challenge for businesses is the ever increasing amount of data-related concepts and terms. Worse, businesses just do not know if data-focused solutions will get them out of their data predicament. Indeed, many businesses are bombarded by this jargon by technology vendors resulting in more confusion than insights.

In years past, there were only a few terms describing business data. Technology gurus started calling this new data phenomenon  “big data” that businesses needed to store 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?

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

Software has revolutionized the business world, but let’s look and see if it may be part of the problem in this age of
“Big Data”. Traditionally, software has merely treated data as an input or output, not the central player, essentially sidelining data as an operational by-product. This continued with the rise of enterprise software and Software as a Service (SaaS) platforms. Businesses have adopted these systems over time, but these systems still tend to treat data as a by-product.

As a result, many businesses now have aging software data silos. To confront this issue, businesses have turned to Business Intelligence (BI) tools to unify these scattered data sources. However, this often seems like a patchwork fix rather than a strategic move.

Exploring the Impact of Monolithic Applications and Emerging Technologies on Data Disintegration.

So it is fair to say, many businesses have become too application-centric. Further, this mindset deters businesses from real insights from their precious business data. Specifically, this is because a lot of businesses are dealing with several monolithic software applications generating huge amounts of data. As an example, many supply chain managers have to work with systems like ERP, TMS, WMS, OMS, CRM, Procurement, SCM, Invoicing, Accounting, SCP, and so on. Worse, now more emerging technologies such as Internet of Things (IoT) devices are generating gobs of new data. And to top it off, there is AI that requires large, quality data sets to work. However, the data AI needs is stuck in data silos, fragmented, inaccurate, and duplicated.

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

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, and is a challenge to implement without business buy-in. 

So first and foremost, businesses would need to adopt a “data centric” mindset. Indeed, this is a key first step is for businesses to really start getting insights from their data and become more competitive. Basically, they need to start thinking of their data as a product, not a by-product. Further, businesses need to think of their data as a tangible and permanent asset. Lastly, they need to think of their software as temporary in that it comes and goes over the years. Indeed, this type of mindset starts businesses on the path to real data insights.

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

Della Shea

So What Does Data Centric Mean And Can It Help My Business?

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 it would probably be obsolete.

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

Data Centric Definition

“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 it simple, and will continue to innovate. Moreover, data silos, information duplication, and data inaccuracies will fade away.  For more details on the benefits of a data centric business, see my article, A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation.

Click here to explore the benefits of this approach, how it differs from data-driven, and how to balance application-centric and data-centric approaches. It’s time to re-think your business’ data strategy!

For more articles from SC Tech Insights’, see postings on data.