6 Biggest Data Governance Challenges in Dynamics 365 ERP and What You Can Do About Them

according to Dun and Bradstreet reportIn the next 60 minutes, 211 companies will move, 743 new companies will open, 429 business phone numbers will be changed or disconnected, 12 companies will declare bankruptcy, 13 companies will change their names. Imagine what this might mean for the data in your Dynamics 365 ERP. When data is constantly changing and evolving, it is difficult to keep it accurate. If your organization is struggling to use data effectively, manage risks and reduce costs, then implementing data management becomes critical.

At To-Ex, we’ve been helping organizations deliver consistent and reliable data. Our solutions enable data hosts and data owners to manage the creation, validation, and distribution of master data within Dynamics 365 F & SCM companies and across systems external to Dynamics 365 F & SCM.

You may have collected a lot of data already, but if you want to make good use of it, you need to know how to control the data. Data governance comes with its own set of challenges. While these challenges are not the same for every organization, there are some that they have in common. This article will introduce you to data governance and its common challenges.

What is data governance?

Data governance is defined as a set of policies, processes, roles, standards and metrics that ensure effective use of information to enable an organization to achieve its goals. It decides who can take action on the data, in what situation, and what methods. (Bryant Bent, Data Governance for Contemporary Firms and Practitioners)

A good data management solution will cover the following four components:

  • Data Distribution and Integration
  • data quality
  • Field Security Administration
  • Data entry workflow

Below is a snapshot of data governance and Master Data Management (MDM) Solutions A portfolio designed for organizations using Dynamics 365 F & SCM (formerly Dynamics 365 F&O).

MDM Solutions Group

Did you know that 71% of business leaders attribute improved customer retention rates and 58% attribute the increase in revenue to good data governance? (Harvard Business Review, 2019).

As the volume and variety of data increases, so will the challenges of managing data efficiently.

6 Common Challenges in Data Management

Challenge One: Lack of Data Ownership

Data management is IT responsibility! Have you heard this before? Many organizations believe that data management is the responsibility of the IT team while others are just data users. This is a myth that must be dispelled.

Expecting IT to allocate resources puts a lot of pressure on one team because they don’t have the time to manage all the data.

The solution: While information technology is responsible for the technology required in the production and use of data, business users must take responsibility for working with information technology to determine data requirements and use it for decision-making purposes. As a best practice, obtain approval from the senior management team before implementing data governance. Each person who uses the data must take responsibility for how they use the data, and this is not the sole responsibility of the IT team and data administrators. It is a good idea to have a team in place to lead your governance initiative.

Challenge Two: Unintended Data Repositories

A data silo refers to stored data that is available only to a few teams, business units, or individuals and not to the entire organization. Data warehouses are often created unintentionally. For example, a product management team can have multiple spreadsheets containing product information and a similar spreadsheet can also be used in sales and marketing. Result – Different teams may end up with different versions of product information.

The solution: Dynamics 365 F & SCM ERP allows data export to disassemble your data warehouses. But you need to make sure that no new data repositories are created. With master data management and data governance solutions in place, you can ensure a single source of truth is provided to the entire organization.

The third challenge: Dealing with poor quality data

Organizations with outdated local systems have to deal with them more often bad data This is not standardized and classified. Instead, it spreads across different local systems.

Consider the example of a retailer who stores online sales data in one system and actual sales data in another. In one system, the income earned by the retail firm is called revenue, and on the other, it is called sales. Now imagine the challenge if a company decides to conduct analyzes on its total income. Although both Revenue and Sales are data fields that indicate a company’s income, there is confusion as the metadata are different.

While this was just a simple example, poor data quality can cause bigger problems when it comes to sensitive data and its handling.

The solution: Data quality is the cornerstone of data-driven organizations. While Data Quality Tools It can help correct past mistakes, a proper governance framework can ensure data standardization, and the right people are assigned to work on the right processes to maintain data quality. It also takes care of establishing the correct rules and processes for collecting trustworthy data.

Fourth challenge: Lack of data control

Lack of control over enterprise data is one of the most common data management challenges. The sheer volume of data available in organizations today makes it difficult to find and control access to the right data. In the absence of data control, duplicate and inaccurate data (caused by human error) increases, which leads to incorrect data transmission, misleading decisions, skewed data analysis and inefficiency of business operations. For example, if an organization has branch offices in multiple locations and employees in each office make changes to legal entities due to the lack of data control policies, this can turn into greater data management challenges.

Organizations want to ensure that the right people oversee the creation of the master data, and they also want to be able to control the distribution of this master data that is generated.

The solution: A data governance framework can define how and where data is used. Global organizations with offices in multiple locations need to control global and local data. Different permissions can be set depending on whether the business user needs to access global or local data. When you want to prevent certain master data fields from being changed locally, you can specify the group of people that should not have access. But doing this using the standard security feature of Dynamics 365 F & SCM is daunting. A data management solution can let you control who adds data to specific fields and enable centralized governance.

Challenge 5: Take a one-size-fits-all approach

With an increasing number of organizations moving to the cloud, it is not possible to deploy data management software designed for on-premises IT infrastructure to cloud infrastructure. Within the cloud there can be different storage solutions containing different data structures (eg files, tables, images) and this makes governance difficult.

The solution: Cloud data governance requires new design and implementation. cloud services It can be categorized into three delivery models: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).

Depending on the model, business users will have different levels of control over their data and each model will require a different approach to governance.

Challenge 6: Constraints of Data Integrity and Distribution in the D365 ERP

When an organization has multiple internal systems (eg, CRM, ERP, HRIS), or is going through mergers and acquisitions, there are bound to be problems with data integration and distribution. Standard Microsoft Dynamics 365 tools have limitations when it comes to data integration and distribution.

solution: The data governance framework helps you create a unified view across the organization and provides a single source of truth. Data policies define how technology and solutions are used.

At To-Increase, we provide solutions such as call studioand Master Data Management Studio and Data Quality Studio to deal with challenges in data integration, distribution and quality.

Who needs data management?

If your organization does not anticipate any changes to master data or does not respond to dynamic changes in the market, you do not need data management. If your organization runs a simple business, does not have multiple branches, and does not deal with important information, then you do not need it.

Let’s say you are a global manufacturing organization with branches in multiple locations. If you do not communicate your product specifications clearly across all branches and do not have policies in place to control data, it can lead to lost opportunities or business losses. That is why it becomes important to implement governance properly.

Any organization that needs to update master data to meet ever-changing business needs will need data management.

How do you properly implement data governance?

Large organizations that use Dynamics 365 ERP typically have and track a data governance strategy Best practices for implementing master data management. In small or medium-sized organizations, this may not always be the case. You may need to set up your initiative for one company within the D365 F & SCM before moving on to the next company.

you can always Talk to an expert To understand the options available to you for starting your own data governance initiative. As you begin with your initiative, you may be asked to tackle some of these and some others, head-on. Instead of using manual effort to simplify your data, consider automation with MDM solutions that take care of the mundane tasks of governance and allow you to focus on the more important tasks that fuel organizational growth.

To see how To-Improvement’s data governance solutions built into Dynamics 365 F & SCM can help your business, download this factsheet.


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