Your business runs on data i.e. if you have realized it. You may however not have moved to making decision using data. Maybe you still rely on general knowledge to make day-to-day decisions.

Maybe you think you don’t have enough data to use for decision making.

You think that only big corporations are the ones who have this opportunity.

If you are proactive, you have started looking at externally-available data to supplement your lack.

Externally sourced data can include economic projections, market analyses, population data etc.

although these are equally important, the most important data is the one already in the hands of your business.

TYPES OF DATA

As long as your business has existed for some time, even 6 months, and has done some transactions, it has data. This is basically what defines the business and its processes.

For the purposes of Master Data Management, we will talk about the data referred to as Master Data.

This is quite different from the normal data which forms daily transactions.

Master Data is the core data which does not change quickly. It is the data which is essential for operations in your business as well as analytical decision making.

Although different businesses will have different types of master data, the below can be found in most of them.

Customer Data

You might view this as the most important of all data.

Such a conclusion can be based on the fact that your customers make the business stand and thrive.

Customers are easily seen as the major players in a business.

These are the people other businesses are competing against you to get. The more customers your business has, the bigger the market share you’ll have. The bigger the market share, the more the profits.

Customer data may include customer name, contact details, date of birth, shopping trends etc.

Sales Data

Customers bring about sales. They like your product or service and they buy. The data about those sales are also key in your business.

There is a close connection between sales data and customer data. The shopping trends contained in customer data are more or less the same as sales data.

However, sales data can take on a more detailed nature.

The details under sales data may include invoice number, invoice date, delivery note number, quantity sold, sale amount etc.

Product Data

Anywhere there are sales, there must be products. If your business provides services, this can be services data.

Your products are what get transferred to customers and the transaction becomes a sale.

Product data serves manufacturers very well.

For them, this can include dimensions, weight, color, packaging quantity, batch number, production date, expiry date etc.

Employee Data

Despite the customer and sales data being very important, your employee data is also critical. Your employees are really the ones keeping the company wheels rolling.

This can be well seen in the customer service, marketing and sales departments.

The people who interact with the customers are the ones who make them customers in the first place.

Otherwise, you could be talking about leads.

Employee data can include employment date, date of birth, leave days, salary information, department name etc.

Asset Data

Assets are easily recognizable as the hardware of the business. Land, buildings, computers and the like, can be quickly referred to when talking about assets.

But apart from these, more examples of assets can include “non-hardware” materials. These can include cash, shares in other companies and debtors.

Data about the tangible assets can include year of purchase, purchase amount, depreciation rate etc.

Types of data can vary widely. Any part of a business can have data about it captured in one way or another.

And this is the data that is very valuable to your business.

MASTER DATA MANAGEMENT

Since there is a lot of data to be handled and utilized for your business to grow, there comes a need to manage it.

The management of data is nothing really new or difficult. For many years, business have been using spreadsheet applications to manage their data.

But data management was never easy using those applications.

When everyone is having the data they need in their computers and share it through email, efficiency is greatly reduced.

More than that, one department’s data may not be the same as another department’s.

This can happen even when both sets of data are about a similar part of the business.

Problem Scenario

For example, the sales department may have the updated address of a customer. They may email this to the dispatch department for deliveries to the right address.

But finance may not have the same information.

When it comes to billing, the invoice may be sent to the wrong address.

This will make collections problematic and your business loses in resources and time.

Master Data Management defined

The above scenario is quite common in large organizations. It can also be experienced in small but busy companies where everyone is busy doing their job.

This is where Master Data Management (MDM) comes in.

Master Data Management

Source: OpenPR

As the name implies, MDM is an implementation of a business-wide system where everyone gets their information from the same place.

A central repository is created and all requests for data are satisfied from that one point.

For this to work, the data will have to come from the individual employees and departments.

The system will however integrate the individual departments so that changes made by one person reflects in the system. This way, anyone seeking the information from the system gets the updated version.

Let’s look at this using the example scenario above. The sales team interacts with the customer and receives an update about her new address.

When this change is updated in the system, it is reflected across the entire system.

When the dispatch team looks up the address from the system, what they get is the new address.

Similarly, when finance is billing, what they get from the system is the new address.

This is the essence of an MDM system.

PRINCIPLES OF MASTER DATA MANAGEMENT

That may sound great, making you see immediately the need for your business to embrace it. Or if you are an IT manager, you already see the benefit of providing such a solution to your company.

But the success of an MDM solution is never automatic. There are decisions to be made and major considerations which influence the decisions.

To help you appreciate the fullness of an MDM solution, we will look at the principles guiding a successful implementation.

Then we will go through some common mistakes many businesses make so you know what pitfalls to avoid.

Lastly, you will see some real-life examples of how MDM works. The examples provided are an everyday part of life.

But from what you will have learned by then, you will appreciate the effort that went into making those examples work.

Data Integrity

The output of any system is only as good as its input. If you put in the right thing, you get the right thing. It is this accuracy that is referred to as data integrity.

As you have seen, and going by the very name of the topic, data is at the center of MDM.

And if the data which is relied upon by all the departments is inaccurate, then everyone suffers.

As mentioned at the beginning, data is needed to make the right decisions. This is mainly facilitated by report generation. The system will generate reports based on the data it has been fed with.

The system may for example indicate that there are 480 pieces of the product which you sell. You may then decide to reduce production so as to avoid overproduction.

This is a business decision which has obvious implications.

On the ground, you may have 400 pieces and not 480. If you sell 370 pieces then get an order for 100 more, you may think that you have the stock for it. And this is where the problem will come in.

You may either think that stock has been lost or find out that the wrong data was entered. Your order may be delayed as you restart production.

The customer may also become inconvenienced because of the delayed delivery. This is a clear demonstration of the importance of accuracy in data entry.

In the same way, MDM is affected by such mistakes.

This is why data integrity is a must. When building the repository, the data must be checked for accuracy and consistency.

Where variations are found, the correct version should be identified and used.

Data Governance

Closely related to data integrity is data governance. Data governance is simply the act of ensuring continued data integrity.

Data governance is concerned with the integrity of all the data that is entered into the system well after the MDM solution is in place. Data governance is usually implemented as a program.

That however does not make it an external part of the process.

Data governance is basically the maintenance of the system. It comes with rules determining the format in which the data is to be in, the process to be followed and in some cases, even the frequency of data entry.

These are rules which are set to uniquely fit individual needs. If your company is constantly adding new types of products, then you can remove the restrictions accordingly.

But certain types of data, for example under the finance department, should ideally have restrictions.

For example, if there are no restrictions, an employee could create fictitious company accounts.

These can be used to channel payments for non-existent transactions.

Change Management and Accountability

The data in the system is never completely unchanging.

There will be instances when changes need to be made. The customer address scenario above is a good example.

But that doesn’t mean that data changes can be done by just anyone at any time. Accountability must be enforced to protect the integrity of the system.

Ideally, there should be one person in every department who is mandated with the role of making changes. This helps in ensuring that the number of people accessing the core of the system are reduced.

For example, you might have 5 sales representatives who go to the field. If one gets an update about a customer’s information, he should pass it on to another staff who has the system rights to make the changes.

In the right implementation, each one of these employees could have a view of the customer data. But their limited rights should not enable them to make changes.

Auditability

Audits should not only happen in the finance department, but also on the MDM system. Auditability in this case refers mainly to the proof of the processes followed while making changes into the system.

If for example a new company is to be created in the system, there should be an approval process followed. If a customer is to be created, there should be an approval granted for the same.

This will provide the records to show what exactly happens behind the scenes.

For auditability to work, data governance has to be in place. With the rules set for new data and data changes, the integrity of the whole system can be maintained.

This then guarantees the correctness of the reports which are generated by the system.

COMMON MISTAKES IN MASTER DATA MANAGEMENT

The implementation of a Master Data Management solution is never an easy one. This is usually work which involves many people and the project itself needs to be managed well.

Many failures come from challenges which can be traced down to the people involved. In most cases, these people are the staff where the MDM solution is being implemented.

Here are some of the common mistakes in MDM implementation.

Ignoring Data Quality

The need for accurate data to be entered into the MDM system cannot be overemphasized. Data is key to business growth and MDM is all about managing that data.

As you clean up data through checks and confirmations where necessary, you lay the foundation of a strong system. When this is ignored, then you have a disaster waiting to happen.

Ignoring data quality happens mostly due to the rush to implement the solution. You may embrace MDM because you have seen the need for it.

But that does not mean that you should hurriedly implement it.

Though desiring to solve the problem as soon as possible, rushing will only set you up for big problems later. Problems which can be loss-causing.

Lack of Data Governance

Once you have ensured the data is clean, the standard has to be maintained. The clean data must be protected by rules and policies. These should determine who can do what, when and to what extent.

This is the realm of data governance. The people working in data governance are called data stewards. Their job is to ensure data quality is maintained.

Accuracy should always be a guarantee if at all the system is to provide the expected results.

The Silo Mentality in Data Governance

Data governance often suffers from the silo mentality. Just as the business can suffer from this at a corporate level, so can the MDM system.

The silo mentality is a description of the situation whereby a business unit works independently of the other units. This is very common in large organizations where there are no deliberate efforts to keep everyone moving together.

Silo Farming

Source: Marketoonist

In the MDM context, this becomes a reality when one department always abides by the rules of data governance.

They make changes accordingly and follow the right processes. All the data coming from that source is always accurate.

The other departments may not be doing the same thing. One common excuse is that the staff are busy. Too busy to follow the right procedures.

At times, even too busy to input the data they need to input into the system.

Whereas the cooperative department can enjoy accurate reports coming from their data, the others one will not.

They will not be able to depend on system reports since they know the data is not accurate. The work may pend and become an unmanageable pile.

Yet that’s not all. Since the cooperative department is not a company on its own, they’ll need data from the others.

The data coming from the other departments or business units will eventually affect an aspect of this particular department’s work.

This will lead to the MDM solution being rejected because apparently, it is not working. Or it has just worsened the situation.

It is important that you work towards breaking the silo mentality.

Assuming That Data Governance is an IT Job

Many employees assume that because MDM is a technical solution, then data governance is an IT job.

They reason that their role is to produce, or sell, or work on finances etc, according to the department they are in.

But what is rarely realized is that the IT department doesn’t create any data.

As such, it cannot know what is accurate and what is not.

For example, from the scenario we’ve used in this article, how could IT know that the customer changed his address? IT doesn’t even have the customer’s contacts to confirm.

Every department should embrace the system and own it. They should also take responsibility of the portions of the system which they are required to work on.

Seeking to Implement MDM in a Single Phase

MDM implementation is not a solution to be implemented at once. Such a move will be too costly in many ways. The project will therefore not prove profitable and is likely to be rejected at a very early stage.

One reason for this outcome is that the process will be tiring for the employees.

For success, there are many things to be done. All employees have to be involved from the beginning so as to understand the data needs of everyone. Training is also a must.

When implementation is being done in one phase, there will be a lot of work to be done.

The staff will have to make adjustments to their daily routines.

At the same time, not many people are able to quickly adapt to a new system.

The employees will start withdrawing and their interest will wane. The whole process will then be seen to be a burden instead of a solution. This is avoided by splitting the implementation of the project into phases.

When you work in phases, you also get an opportunity to use the installed phase and measure the benefits.

Once you see how your Return On Investment can come about in the future, you can invest into the rest of the phases.

Neglecting Data Security

Master Data Management is all about data and data is at the core of every business.

All over the world, the target of many cyberattacks is business data. And these attacks are coming in the form of ransomware attacks.

When your data is captured, you may not know what might come.

When the attackers ask for money, you are likely to pay up because you know the value of your data.

In any case, your production might as well have stopped since the system is hijacked..

Just think of the damage your business could experience if your data was to be released into the public.

What would happen when your competitors knew how much you bought your raw materials and from who? What if they knew the chemicals you use to make your products as durable as they are? Or maybe they get access to the email correspondence of senior executives with your business strategy details?

Any of these situations could pose a threat to your business.

Securing your data is as important as having a PIN for your debit and credit cards. It is as important as keeping your windows rolled up when your car is parked.

You have to set your system with security policies and create users who have defined roles. No two roles should overlap so that accountability can be guaranteed.

Not everyone needs the access rights to all data. In some cases, staff can view but not change the data records.

You should also train your employees on securing their computers. They should use strong passwords and avoid using their smartphones to work.

This is unless they have taken measures to safeguard the data contained in their phones.

EXAMPLES OF MDM IMPLEMENTATIONS

With all that theory, let’s look at how an MDM implementation looks like.

Large organizations implement MDM at a larger scale and can have challenges which differ from small organizations.

Still, there are success stories in your daily life which you have certainly interacted with.

Online Marketing Systems

You have definitely done some online shopping. If not, you at least are aware of Amazon.

As a customer however, you may not understand how everything happens behind the scenes.

You may buy some books and after a few days, you get an email informing you about another book tackling a similar subject. Upon visiting the website, you see other books of related subjects and you’re interested in buying.

A big part of this is marketing.

However, the real power lies in the data available to the system. Although much of it happens automatically, the process is quite simple.

Your first visit was tracked and information fed into the system. Your purchase was used to determine what other products could attract your attention. You got the communication and ended up buying more.

Transfer this to a brick and mortar store. What you have is an active salesperson engaging you. He helps you make a buying decision and leads you to the cashier (finance department) to pay. Y

our details as found in the system were then used to deliver the product (deliveries department) to your home.

The information you gave the sales person while registering was used to create an account (customer relationship department) with all the relevant details.

After the purchase, the marketing department didn’t need to ask the sales team anything about you.

They access the system and get fresh data about a new customer. They relate your purchase to other products and send you an email using the provided address.

So the sales, finance, delivery and marketing departments got what they needed from the same place.

Phonebook Application System

Your smartphone has another good example of an MDM solution.

This is implemented in your phonebook application. Your phonebook can store all the necessary information about a contact.

These can include names, email address, different phone numbers etc.

You also have an email program in your phone. From it, you can create addresses.

But you don’t really need to. If you are sending an email to someone in your phonebook, you can get their address from there. This removes the need for creating a contact twice.

That same information entered into your phonebook is utilized by the messaging app. And other downloaded programs e.g. WhatsApp will also make use of the same information.

Can you imagine what would happen if you needed to create contacts for all these programs? That would be too much duplication.

That would really slow you down. You could also have an updated contact on one program while the others contain wrong details.

Such is the benefit of having an MDM system in place.

CONCLUSION

Master Data Management is a solution which is needed in every business. If you want to make the right decisions in your business, utilize data.

And for the effective utilization of data, work on having an MDM system in place.

Master Data Management: Definition, Principles, Common Mistakes, Examples

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