tmdc logo white
tmdc logo dark

Aligning Data Strategy with Business Strategy


Everyone knows that data is an important component of managing a successful business today. Yet many companies fail to fully align their data strategies with their business strategies, leading to disconnects that are quite painful. Some examples from the past year’s retail sales challenges provide firm evidence of how failing to have a company’s business and data strategies fully aligned can lead to negative business impacts. Let’s look at what happened and then explore what companies can do to avoid the same situation in the future.


From Famine to Feast

It doesn’t seem that long ago that retailers everywhere were struggling to keep shelves stocked. Many necessary products such as paper towels and baby formula went out of stock for long periods nationwide. Not only were retailers and manufacturers losing money because they didn’t have products to sell, but customers were frustrated and, in the case of items like baby formula, even scared.

What a difference a little time can make! Recently, a slew of earnings reports reflected trouble retailers have faced with an overabundance of stock on many items. Yes, you read that right…we went from empty shelves to overflowing shelves and bursting stockrooms for many items. There were distribution centers packed more than 90% full, which isn’t healthy as it limits flexibility in bringing in new items and implies high carrying costs for slow moving inventory.

For consumers, this abundance is a welcome relief, but for retailers, it can be almost as costly as having too little inventory. Multiple retailers have had to offer customers significant markdowns to move products off the shelves and out of stockrooms, which eroded margins significantly.


What Caused the Problems?

To be fair, there were a wide range of problems that led to the supply issues, many of which were out of the retailers’ control. Obviously, the global responses to COVID-19 initially caused massive delays in shipments and distribution of products to stores. Once stores reopened and the supply chain improved, customers started buying like crazy. However, some of those buying patterns couldn’t continue indefinitely.

For example, in 2020 many people rushed to buy TVs and other electronics since they would be stuck at home more than usual. But those products tend to last a long time and, eventually, there weren’t enough buyers to maintain the blistering sales rates. To make matters worse, fears of an economic downturn and massive inflation have made customers become more reserved in their spending in recent months. The trends combined to make inventories based upon prior projections much too high. But by the time the retailers recognized the shifts in the market, they were stuck with too much product. Without a highly responsive data strategy in place, reactions were too slow and business impacts were too high.


Is There a Way This Could Have Been Avoided?

At least partially, yes! Better collection of data across the supply chain combined with better analytics can better prepare manufacturers and retailers to handle disruptions. Companies can do better by actively tracking the performance of every part of the supply chain, identifying bottlenecks, shortages, or overstocks as soon as (or before!) they begin and incorporating external data to identify broader community trends before they manifest themselves in sales figures.

The earlier that a market disruption or deviation from forecast can be identified, the faster that steps can be taken. These steps might include reducing orders, redirecting shipments, or changing product mix. To be effective, the analytics must not only allow analysis of what is happening but must have robust simulation and projection capabilities so that the impacts of potential actions can be understood. Of course, to do all of that is neither easy nor effortless. Priority must be placed on the collection, governance, and analysis of a wide range of data. Corporate infrastructures to support those activities must be more flexible than in the past and must be able to change quickly as business requirements change.

If that sounds like a tall order, it is! However, there are technologies available today that can help retailers and manufacturers better manage their supply chains to avoid some of the big hits that businesses have taken in the past few years. These technologies also make it easier to strongly align a business strategy with a data strategy.


Data Operating Systems to the Rescue

Data operating systems are one of the newest technologies on the market, and DataOS from The Modern Data Company is the leader in the space today. A data operating system lays connective tissue between all your current systems, whether legacy or new. DataOS will provide a unified catalog of all available supply chain data across the enterprise and enable users to query and analyze the underlying data without having to worry about where it resides.

A data operating system can enable the implementation of a world class supply chain platform. Regardless of the volume and variety of supply chain data that your organization may have, DataOS can bring it together to help you better understand and manage your supply chain. From that understanding, you can deploy programs and contingency plans that develop the resilience, efficiency, and flexibility you are seeking. As you seek to harden your supply chain against disruptions, DataOS can provide the scale and functionality that you require to improve your initial forecasts and respond more quickly when reality deviates from those forecasts. It can bring your data strategy fully in alignment with your business strategy.

Learn more in our e-book, The Latest Look in Retail – Powering Sales and Strategy with Advanced Analytics.

Subscribe to
Our Blog

Be the first to know about the latest insights from Modern.

People Also Read

Latest Resources

The Modern Data Company Brief

The Modern Data Company Brief

The Modern Data Company BriefThe Modern Data Company is radically simplifying data architecture with its paradigm-shifting data operating system, DataOS. We're replacing overwhelm with composability, reinventing governance, and connecting legacy systems to your newest...

DataOS – The Data Product Platform

DataOS – The Data Product Platform

DataOS® – The Data Product PlatformDataOS is the The Data Product Platform pioneered to enable data teams to create, deploy, and manage self-sufficient enterprise-grade data products. These data products are reusable, composable, and compatible across any data stack,...

DataOS and Snowflake – Better Together

DataOS and Snowflake – Better Together

Not Getting Value from Your Data Transformation? Fix itImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV. In the past, organizations have struggled...

DataOS® Solution: AI/ML360

DataOS® Solution: AI/ML360

DataOS® Solution:AI/ML 70% of AI initiatives fail and teams spend the vast majority of their time simply prepping data for platforms, leaving very little left over for gaining insights and driving business value. But an AI/ML platform powered by DataOS can achieve...