Master Data Management - what and why?

 

Master Data Management has been on the agenda for many companies for some years now, but only in recent years has there been particular focus on introducing management of the company’s Master Data as a discipline.

This is because new systems are implemented to a greater degree and data accessibility and volumes are generally increasing. The importance of having correct data is not new; however, the complexity is gradually increasing, which leaves companies without proper control. This results in a solution that often involves a lot of manual and neglected work.

Before we get started, let’s just quickly agree on what Master Data Management actually is. Let’s split it up in two: “Master Data” and “Management”.

Master Data

Master Data constitutes a company’s core information, e.g. on customers, suppliers, products, employees, etc. (Let’s call these data objects at this stage). For example, the information tells us something about the individual data objects’ identity, affiliation, etc. (name, address, company reg. no., telephone no. email, website, etc.) and is often to a large extent statistical; however it can change over time, for instance in connection with address changes, name changes, turnover, etc. It is often also information that is used in many different systems, which means that there is a certain risk for redundant data and duplicate data.

This master data is created and used widely across the organisation, and it is the basis for the data in the company’s business processes, e.g. procurement, sales, logistics, marketing, finance and HR. In other words, it is an important asset for all companies.

Management

• It kills your marketing campaigns
  If your message does not reach the right people due to incorrect contact information, your campaign falls apart

• It reduces customer satisfaction and trust in your company
  If your customers do not receive relevant information through their preferred communications channels, they will find other alternatives
• It harms your brand’s reputation
  If your data is imprecise, your workflows will be ineffective and unstructured, and you will risk bombarding customers based on duplicate contact data
• It affects lead generation
  Leads fail due regularly outdated data
• This results in the inability to make informed decisions
  Incorrect data also makes it difficult to make decisions that benefit the company going forward
• This leads to lost business opportunities
  If your marketing efforts do not connect with and involve your target group due to poor quality data, you will miss opportunities

• Dispersed data
  Data is spread over a large number of different systems and applications, and it is available in many areas that the company is not fully aware of
• Incomplete data
  A lack of data and data updates results in a risk of drawing wrong conclusions in analyses and problems in operational tasks that are dependent on complete data
• A lack of common terms
  A lack of clear, understandable business definitions can result in misunderstandings across businesses. This makes it difficult know when data is correct and accurate.
• Redundancy and duplicate data
  Redundant data leads to confusion and more work. Companies do not know which data is “the right data”, and this can lead to errors and deficiencies in deliveries and interactions with partners.
• Lack of integrations
  A lack of integrations between systems means that employees must perform manual updates in several places, and the need for management and control is doubled for every system.
• Lack of funding
  High costs for creation, update, data cleaning, etc. make it difficult to get internal funding, which means that the work is often not prioritised and the task grows over time.
• Lack of organisational ownership
  Lack of ownership and responsibility for data leads to a risk that the tasks are neglected and increases the likelihood of poor data quality.

• Golden Record
• Quality measurement and overview
• Governance – policies, rules and guidelines
• Governance – organisation, roles and responsibility
• Best practice – do’s and don’ts