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Note this the second installment in a series of posts on how master data management affect a company’s financial health. In my first post, I explored whether Wall Street should care about your master data management strategy.
Fiscal responsibility is core to the makeup of all corporations, whether public or private. In addition to Market, Income Statement, and Balance Sheet information, we monitor financial health through a series of ratios such as liquidity, leverage, coverage, operating, and expense to sales. And more recently a significant amount of energy has been focused on improving the cash-to-cash cycle times of our businesses. Furthermore, measures like Net Promoter Score or NPS have taken center stage when considering the growth and market share prospects of any corporation.
Achieving top quartile performance across these financial measures, which in turn directly drives indicators such as earnings per share, requires a business outcome-oriented MDM strategy and platform. Traditional ERP technologies have struggled to formulate such as strategy, let alone execute it. Yet a new generation of cloud-based network platforms have emerged and risen to meet the task.
A MDM strategy enabled with today’s cloud-based network platforms begins with the basic premise that healthy financials are driven and sustained by a healthy relationship with our customers. We go to great lengths in protecting our relationships with both our customers and suppliers in order to be sure we can satisfy the actual demand at the right time in the right location. But what are the hidden costs of providing these higher levels of customer service?
In order to manage the risks associated with lead times and variability in our supply networks, corporations invest in both physical assets as well as additional operating expenses in order to protect their ability to serve actual customer demand at the right time in the right location. These investments are a necessary by-product of an ERP style architecture that forces multiple enterprise silos to plan, forecast, order, replenish, ship, reconcile and invoice across multiple parties through various supply network echelons in order to satisfy the actual consumer demand signal…..which from an NPS perspective is really the only independent variable across the entire network.
This is where MDM comes in. From a business performance perspective, fragmented and inconsistent data negatively affects cross-sell/up-sell, delays time to market, creates supply chain inefficiencies and weakens a corporation’s overall market penetration. When customer data has duplicates, is incomplete, or just generally inaccurate, companies will experience problems in revenue recognition, risk management, marketing and customer loyalty.
In later posts I will explore in detail the connection between MDM and a company’s fiscal health….it’s significant enough that even financial analysts have started to take notice. In an example I’ll cover in greater detail later, a One Network customer that operationalized our cloud-based MDM strategy saw financial benefits translated into quarterly EPS results which beat Wall Street’s expectations by an order of magnitude!
But if you’re impatient and want to find out more now, I suggest you read the new white paper: Why Wall Street Cares About Your Master Data Management Strategy
- Generative AI: Force Multiplier for Autonomous Supply Chain Management - May 23, 2024
- Top 5 Signs Your Supply Chain is Dysfunctional - August 19, 2022
- Why a Network Model Makes Sense for Automotive Suppliers - July 30, 2019