In 2017, The Economist came out with a very catchy title – “The World’s Most Valuable Resource Isn’t Oil Anymore, but Data”. Nowadays, businesses thrive on data. In fact, this intangible asset is the very foundation of analytics. That’s what ultimately towers an organization above the competition.
Gaining valuable insights about the overall direction, consumer demand, business processes, and stability of your firm can make it or break it for you. For the management to make fact-based decisions, data analysts invest a considerable amount of time to process and analyze tons of information on a daily basis.
So, how do companies acquire data exactly? Even more so – how do they ensure data quality and accessibility?
This is where the master data governance function has proven to be extremely useful.
What is Master Data?
Master data (also known as Standing data) refers to unique data attributes in an organization that are non-transactional in nature.
In essence, this is data about the major business objects, such as products, customers, suppliers, costs, and others. Think of Master Data as “data about the data”, or the “alphabet” of business transactions that business and data analysts tackle daily.
An organization uses standing data across a variety of platforms and technologies and ideally, it should manage it consistently. Duplicate master data entries, such as two customers with identical customer numbers, could cause problems with transactions and reporting.
Why Is Master Data Governance Important?
A brief data governance definition would be “a system that concerns people, processes, and technologies involved in managing data”. More specifically, it defines who, within an organization, has control over certain information and how different parties can put these facts and figures to use. Besides, it helps us store and organize data properly to allow for easy and efficient extraction of information from a single source of truth. This is another essential aspect of a firm’s data governance framework.
Combined with a proper data governance system, master data governance delivers the right information to the right users at the right time. Not only that – it provides data in a standard and harmonized way across an organization. As such, master data governance increases the integrity, auditability, accountability, and transparency of a company’s data and turns it into a reliable source for analytics. We can also expect data governance to ensure uniform communication and a common understanding of the metrics across a business.
Master Data Governance: A Practical Example
Let’s consider some leading data governance practices from Coca-Cola.
Coca-Cola operates actively in 200 countries around the world. They manage more than 500 different brands, with millions of customers buying the firm’s products every day. It is hard to imagine how much data Coca-Cola processes per minute. To manage their data more effectively, Coca-Cola introduced an enterprise-wide governance framework with a strategic orientation and enterprise perspective for data and information.
Generally, the responsibility of the master data function includes definition, maintenance, and enforcement of governance policies in accordance with pre-established criteria. In practice, this means that every single product, which is a combination of brand, package type, and size, is clearly captured in the master data. So, Coca-Cola’s analytics team should be able to tell the entire story of that single product with a click or two.
The same applies to customers. The enterprise resource planning (ERP) system used by the company contains valuable information, such as name, address, VAT number, contact details, etc. Coca-Cola’s master data governance framework requires employees to store this information in a predefined manner. Again, the data governance function is responsible for establishing, maintaining, and controlling the consistent implementation of that criteria.
Suppose the master data team has established that you must use capital letters and a dash when entering “COCA-COLA” into the database. If employees don’t follow this guideline, the Coca-Cola brand will appear in 3 incorrect categories when we run a report – Coca-Cola, coca cola, and COCA COLA. Ultimately, this impedes us from running a meaningful, well-structured analysis.
Because of the amount of data Coca-Cola is dealing with, the company assigns data stewards to exercise the data governance process. They are working with local subject matter experts (SME) – sales, supply chain, finance, and business analysts – to improve the reusability, accessibility, and quality of stored information through the implementation of common data standards.
In reality, every department uses some specific terminology, and master data governance must ensure anyone across the organization uses it consistently. For the sales department, we group customers in channels. It can be a HOME channel – when customers consume the products at home; or a COLD channel – when people order their products in cafés and restaurants. Besides, we have the “ON-THE-GO” channel – this may be a non-alcoholic Coca-Cola beverage bought at a gas station.
In this case, consistent customer categorization allows Coca-Cola to better understand and compare how these channels perform against a given benchmark.
For the finance division, we can think of how we aggregate cost in various cost categories. Suppose that we want to track labor costs. This is an item that includes salaries, benefits, incentives, contract labor, vacation pays, social security, and so on. Primarily, the data governance and finance teams are both responsible for defining what is captured in that Cost Category. Furthermore, they should maintain the master data and oversee that these guidelines are consistently followed across the organization.
Setting up these criteria is a rather sensitive task to do, as there are many stakeholders impacted by these decisions. So, firms should make sure that definitions are the result of negotiation and agreement with cross-functional business and technology leaders.
Master Data Governance: Next Steps
Having a well-established master data governance strategy is a critical ingredient for successful analytics projects. Ultimately, you need high-quality data, which means – consistent, easy to access, and categorized master data. Without this, benchmarking and any other analytics exercise will be meaningless. And without business analytics – companies will fail to remain competitive.
Essentially, you can increase efficiency, reduce business risk, remain competitive, and streamline operations with the help of actionable data insights, as long as you have the necessary business analytics expertise and specialized knowledge. So, if you want to master indispensable skills that would contribute to the success of any company, make the first step with our Introduction to Business Analytics course for free.