How Data Quality can Affect Business Processes
How Data Quality Affects Business Processes
Business processes and data quality go hand-in-hand. Any time you access, share, enter, or update data that relates to a business process, you’re using data.
But what if your business processes are relying on poor data? If your data isn’t reliable, the work you do based on it will be inefficient and misguided.
In this piece, we’ll go over:
- The importance of high-quality data.
- The key attributes of a good business process.
- How data quality impacts business processes.
- Establishing a process to ensure high-quality data.
- How data quality impacts specific business sectors.
What is Good Data Quality?
We can call this inaccessible data dirty data because it disturbs processes and impacts relationships.
High-quality data, or clean data, is information that you can rely on to make sound decisions. It is:
- Accurate.
- Consistent.
- Up-to-date.
- Relevant to your business.
- Available to key stakeholders.
- Accessible.
- Secure.
While clean data might be simple, it’s far from easy. Dirty data can arise from just a single error among thousands of processes per day.
Most importantly, high-quality data isn’t just good information, it’s trust in that information. One of the most effective ways to develop that trust is to use a master data management system to continuously check the data quality.
The benefits of master data management for business processes include supporting good data and making it easy to share. Having clean, trusted, accessible data is critical to ensuring your business processes are efficient and reliable.
Key Attributes of Business Process Management?
A business process is any activity or series of activities your business performs to accomplish a certain goal.
Business processes can be informal, like two project managers coming together from partner organizations to figure out the best way to work between them. They can also be formal, like a written, documented process that you share with clients.
Good business processes are:
- Goal-Driven: They are designed to achieve a specific, targeted purpose that supports your business strategy.
- Actionable: A series of clear, viable steps form the foundation of a good process.
- Adaptable: Instead of constantly reinventing the wheel, smart businesses save time and money by adapting current processes to new situations and goals.
- Efficient: Good business processes include optimizations and best practices to save time and money.
These four aspects all rely on good information. That means if you want to improve your business process management (BPM), it’s critical to maintain a high level of data quality.
How can Data Quality Improve Business Processes?
Dirty data at any point in business operations can cause major problems downstream.
Imagine you’ve stumbled upon a better way to share progress updates with a client, but didn’t tell your colleague. From that point onward, your updates look a little bit different from your coworker’s.
The differences seem trivial until you realize that your coworker has been reporting projected sales, while you were reporting actual sales. Even worse, the discrepancy has thrown off the client’s budget for the next quarter.
In this case, a breakdown in a business’s attempt to adapt its processes caused serious problems. Those problems could have been avoided with more consistent data.
Here are some other ways that good data can support the four aspects of a business process.
Business goals are possible with quality data
Processes like fulfilling a customer request, launching a marketing campaign, or selling a new product all require trustworthy data. Without good data, getting the right business outcomes can be difficult or impossible.
On a higher level, it’s quite risky to set an organizational goal that’s fueled by inaccurate information. Business objectives based on bad intel will inevitably waste time and money, and sometimes cause disasters.
Good data makes business processes actionable
If a business process requires accurate, actionable steps, then the data that goes along with it needs to be just as reliable. It’s impossible to take steps forward if you cannot trust the directions.
Not only is this frustrating, it causes major problems downstream. Because business processes are leading towards a larger goal, anything that slows them down ultimately affects the entire business.
High-quality data leads to greater adaptability
Because processes need to be adaptable and updatable to fit ever-changing business goals, the data they rely on needs to be easy to access. MDM systems can help here. They offer flexible ways to view data and offer a single source of truth for your entire organization.
If your data is difficult to access and analyze, you’ll be unable to quickly pivot when the need arises.
Good data makes for efficient workflows
If dirty data lurks in the shadows, it will present itself when it impedes your business processes. If a step in the process requires data that’s missing, you’ll have to pause the entire project while you look for the right information.
The same goes for inaccurate or inaccessible data: The more time you have to spend hunting down or fixing data, the less you spend making actual progress.
Establishing a Process for High-Quality Data
Because good business processes rely on good data, it’s crucial to also establish a business process for data quality.
How will you define good data? How will you maintain it? Have a clear idea of what value your data adds to your company. To do this, you’ll need to establish internal documentation to define what poor quality data looks like and why quality data is crucial to achieving your goals.
Forrester recommends first building a business case for data quality within your organization. Talk to relevant stakeholders like senior leadership, project managers, finance team members, and other data leaders within the organization, to set data quality standards and goals.
Once you’ve agreed upon how your company values and uses data, you can begin to establish processes to maintain it on a regular basis. These include data cleaning, digital transformation (changing the format of the data), and sharing with team members and external partners.
Furthermore, you can begin to identify new processes to support your organization. A modern MDM solution can help you uncover hidden connections within your data sets. Being able to see how your company’s data connects across many layers can show you how these layers interact.
Here’s an example. By tying your product data to individual customer purchases, you can use this information to establish better workflows between product, marketing, and customer service teams. This creates a feedback loop, providing more useful data while also maintaining the quality of that data.
High-Quality Data Supports Business Process Management
Every business in every industry can benefit from better data.
Retail
Companies like CarMax use data tools to inform their business process management. Using Reltio, CarMax was able to identify and establish a process for delivering an end-to-end customer experience with both online and in-person components.
This enabled them to adapt when the COVID-19 pandemic began by pivoting to online customer interactions when the need arose.
Consumer Packaged Goods
High-quality data can help with business process improvement. L’Oreal improved their data management and data quality in a scalable way using an MDM system. This allowed them to both improve their customer journey mapping processes and create consistent customer experiences.
Insurance
Better quality data can lead to faster customer support. Empire Life increased first-call customer signups by 60% by improving their data management.
Build a Data Quality Process with Master Data Management
High-quality data is crucial for every business process and every sector. That’s because data shapes the countless processes that occur each day.
Your workflows depend on trustworthy data, which can only come from improving its quality. That means it’s more important than ever to establish a data quality process by:
- Working with your current team.
- Hiring data experts.
- Using an MDM system like the Reltio Connected Data Platform to create a single, self-cleaning source of truth for all your data.
For more information on how the Reltio platform can support your processes, request a demo today.
