An Introduction to Enterprise Data Management
Your company needs enterprise data management
As a leader in your organization, you may be wondering why you need to concern yourself with enterprise data management. The truth is, diligent maintenance of data impacts every area of your company.
Well-maintained data makes it easier for your company to comply with financial regulations by improving the quality of data you receive, which in turn enables you to confidently make key business decisions.
If you're relying on inconsistent data, your ability to create accurate reports is hindered, mistakes are likely to go unnoticed, and huge amounts of time and resources are wasted.
Enterprise data management can save you time and money and ensure your business stays compliant; this will allow you to deliver more value across your entire company.
What is big data?
According to IBM, 90% of the world's data was created in the last two years alone. This data comes from a huge variety of sources and comprises what is commonly referred to as big data, which is often defined in terms of four categories:
- Volume: the amount of data that is available and collected
- Velocity: the speed at which new data comes in
- Veracity: the accuracy of the data itself
- Variety: the type of data, which can be structured or unstructured
Structured data can be easily organized by whether it's machine-generated or human-generated data; examples include phone numbers, postal codes, social security numbers, and many more. Because of its systematic and logical configuration, structured data is easily searchable in databases.
Unstructured data is anything that doesn't fall under the umbrella of structured data. It has an internal structure but isn't organized in a predefined manner. This could include information coming from text files, social media, websites, videos, images, and more. Gartner estimates that more than 80% of all data is unstructured. Companies are increasingly recognizing the need to manage and maintain this data.
To turn your data, whether unstructured or structured, into an actionable asset, you'll need an enterprise data management platform.
What is enterprise data management?
IBM found that one in three business leaders don't trust the data they have to make decisions. Data collection is important, but it's what you're able to do with that data that truly matters. This is where enterprise data management comes in.
Enterprise data management is the ability of companies to acquire, store, and process data. Many terms are used interchangeably when referring to data management.
One example of this is "data quality" and "data governance"; these two terms, though related, are not the same. Data quality refers to data that is accurate, complete, and consistent with all business rules. Data governance refers to the planning and monitoring of all data assets.
In other words, data governance makes it possible for individuals to find trustworthy data.
Components of enterprise data management
Components of enterprise data management
- Data Governance
- Data Integration
- Master Data Management
- Data Security
According to IDC, most businesses are managing data that is growing at a rate of 40% per year. The variety of structured and unstructured data they are handling is also increasing.
All of this data must be stored in a central location in order to make it accessible to everyone across your organization. This challenge is where enterprise data management becomes essential.
There are several components of enterprise data management; we'll explore each in more detail below.
Data Governance
Data governance looks at the policies and processes a company uses to maintain its data. It establishes a company's data laws and outlines how they are enforced. Data management encompasses three different areas.
- People: If you want to accurately and reliably manage your data, you are going to need to find the right team first. This team will be responsible for managing important aspects of your company's data, so you need to clearly define their roles and what is expected from them.
- Processes: You need to outline a process for how your data will be controlled, audited, and monitored. This will ensure that your data is accurate and useful in any scenario.
- Technology: Technology is not the answer in itself, but it does help. It allows your team to find the resources they need, streamlines your processes, and empowers your company to make accurate, confident business decisions. Data management technology will include things like verification and monitoring tools.
Data Integration
Data integration consolidates a company's data from a variety of different sources into one easily accessible location. This ensures that everyone in the company has access to all relevant data and can leverage it no matter where they are.
Data integration gives you a unified view of all your data, so your company doesn't have any blind spots. It also improves the value of that data over time.
Master Data Management
Master data management (MDM) is a method used to define and manage an organization's data and provide a single point of reference. This helps your company reconcile scattered data from various sources and makes it actionable. When implemented correctly, MDM improves the quality of the data and streamlines it across all departments.
So, while data integration focuses on consolidation and making data accessible, MDM reconciles data from multiple sources and makes it useable.
Data Security
And of course, no data management strategy is complete without data security. This ensures your data is protected not just from hackers, but also from corruption.
Companies are increasingly investing more money into the security of their data. This is because companies are more dependent on software for storing their data than ever before.
Security breaches can't be entirely eliminated, but incidents can be significantly reduced, both in quantity and severity. One of the best ways to avoid security problems in the future is by documenting and learning from mistakes as they occur.
Why your business needs enterprise data management
84% of financial companies recognize that data is integral to their ability to create a business strategy. Companies that don't implement data management strategies are less competitive, risk non-compliance, and may end up losing revenue.
Let's look at five reasons why your company needs data management:
1. Up-to-date data
Data is only valuable if it's relevant and accurate. If it's not monitored, then the validity of that data diminishes considerably, and it stops being useful to your company.
One of the biggest mistakes that companies make is failing to elaborate on how they will maintain the quality of their data. Lacking a structured plan for ongoing maintenance will result in decreased data value over time.
When business owners aren't confident about the quality of their data, additional steps must be taken before it can be used. This is time-consuming and leads to an unnecessary drain of resources in their database.
2. Compliance
As the volume and variety of your data increases, it becomes harder for companies to mitigate compliance risks. This often causes companies to only do the bare minimum required of them.
This kind of approach to data management has obvious flaws. It's a reactive approach to enterprise data management, and while it can cause some types of data to be well-managed, but this does little to create a lasting change in a company's data management practices.
3. Competitive advantage
Companies that have embraced a proactive approach to data management recognize the competitive advantages they gain from it. Data is a core business asset and is worth investing in.
4. Reduced costs
Is a significant percentage of your staff required to dedicate their time to coping with low-quality data instead of focusing on value-add tasks? If so, this is costing your company money. Enterprise data management can help you reduce these costs.
5. Customer service
Low-quality data will almost always lead to a poor customer experience. This could be something small, like a simple mailing error, but could lead to serious mistakes down the road. When you improve your data management strategy, you'll be able to instill long-term loyalty in your customers.
Where do I start?
Before you can implement enterprise data management across your organization, you're going to need a solid, long-term strategy. Here are six steps to help you get started.
1. Define your goals
The outcome of this step will differ for every company because your goals will depend on your starting point and unique business requirements. Start by looking at the systems you already have in place and identify areas where you can improve. Examples of questions to find answers to during this step include:
- Do you have a way to securely share data with other employees?
- Do you have a system in place to back up your data?
- Is your invoice data fully captured?
- Do you have data governance policies for reporting initiatives, such as ESG (Environmental, Social, Governance) compliance or sustainability reporting?
Answering these questions and reviewing relevant policies is a helpful way to identify areas for improvement throughout your company.
2. Educate stakeholders
In order for enterprise data management to work, everyone involved must be on board and fully committed. You'll want to spend time educating all major stakeholders about why data management matters and how it will benefit your company.
3. Start small
Once you have outlined clear goals for improvement, it's best to start with smaller, simpler solutions first. Addressing problems that are easy to fix will help you build momentum as you move on to larger projects. Achieving these types of quick wins is also a good way to boost morale and get other employees interested as well.
4. Choose a relevant solution
Your company's approach to enterprise data management will depend largely on the industry you're in and the realities of your business requirements. In order for your management strategies to be truly effective, your data has to be useful and relevant.
You should continuously look for ways to automate and improve existing processes wherever possible. The goal is to make managing your data as simple and repeatable as you can.
Your AP department may be a good place to start. Accounts payable manages a substantial portion of data within the organization, and the processes and workflows utilized in these departments are still largely manual. Technology can do more than help capture relevant data that benefits the entire organization; it can automate and improve processes, generating considerable savings and operational efficiencies.
5. Choose the right tools
For enterprise data management to be successful, you need to put the right technology in place, so finding the right tools can make or break your initiative. For data acquisition, for example, make sure you select tools that ensure complete data capture with minimal manual intervention. Of course, technology alone won't fix the problem; you must also put processes in place to support the correct use of this technology.
6. Focus on data quality
As we've already stated, it's not about the amount of data that you have, but what you're able to do with it. In some ways, bad data is worse than no data at all. You should focus on maintaining the quality of your data. This is where digital stewardship comes in.
Individuals who should be involved
Having the right individuals in place will be key to the success of your program. Here are a few individuals you should seek out:
Executive leader
You'll need a C-level executive who's willing to sponsor the program and be its cheerleader. This person should be identified as soon as possible because they will have access to resources, staff, and funding that other employees don't have.
Data quality steward
A data quality steward knows how data is collected and maintained. They also understand how this data affects business processes and decisions. This person will act as a central point of contact and will be responsible for maintaining operational systems and data quality.
Data governance leader
A data governance leader is responsible for overseeing and implementing the data management project. This person will act as the middle-man and will help streamline the process of collecting, storing, and protecting data. This person should have excellent communication skills and the ability to stay neutral during discussions or disagreements.
