Unlock Value with Data Management

Introduction

Let’s be honest, anyone can ask ChatGPT “What is Data Management” and get an answer that at first blush seems rather comprehensive.  

‍

Data management refers to the process of collecting, storing, organizing, and maintaining data to ensure it is accurate, accessible, and secure. It encompasses a wide range of practices and technologies aimed at ensuring that data can be used efficiently and effectively in various applications.

‍‍

In this post we will explore several of the key activities.  It is critical that both enterprise business systems owners and users understand how foundational data management is to achieving the full value of an application.  

‍

‍

Using Data

Every organization has a wealth of information (data) with a virtually unlimited number of ways in which to use the data to support business decisions.  As we consider data management, the intended use of the data is absolutely paramount to understand to unlock the full value of the data.  

‍

Let’s consider a real life example.  An organization is designing a website which will include a contact page with a form that allows a visitor to submit a request for a meeting.  There are multiple potential uses of the data in this example.  The marketing team can use the contact information to drive campaigns to increase awareness of a new product or service.  The sales team can use the submission as a lead generation tool to develop new business.  The customer success team can monitor for messages from their existing customers and address questions or concerns more rapidly leading to improved customer satisfaction.  These are just a few examples of the ways in which one set of data may be used by an organization.  

‍

When an organization is developing a data management strategy, it is important to start at the proverbial end.  Understand how the data will be used to make decisions.  Effective data management processes can be designed and deployed ensuring that the data will indeed be useful.

‍

‍

Managing Data Inventory

If we think of data in terms of a product, we can start to apply the concept of inventory management.  Knowing the intended use of our product allows us to begin the process to procure the raw materials needed to create the finished product.

‍

Different sets of data are our raw materials. From where do we source our data?  Does it come from within our organization or do we need to get it from a 3rd party vendor?  These are questions that help us to identify the sources and types of data needed to build our product.  

‍

Once we procure those raw materials, where are we going to store that inventory until the time when we need it in our manufacturing process?  Think of this as our warehouse, not to be conflated with a data warehouse.  In this example, the warehouse is simply our storage facility.  With these types of questions we are answering an important question, where we will store our data?  

‍

Every well run warehouse requires organization.  A company wouldn’t get a shipment of copper wire and not have a plan for where in the warehouse the spools of wire would be stored.  Data is no different.  Just like endless shelves neatly organized with parts needed to create our product, data too needs to be organized.  This is our data catalog.  

‍

Returning to our website example, we know that the data we collect will be used in marketing & sales campaigns as well as customer retention.  These are our finished products.  The raw materials we need to build these finished products are the visitor’s name, the company for whom they work, an email address, ideally a telephone number, and their reason for requesting a meeting.

‍

Next we have to determine where the information the website form collects will be warehoused.  Does it live in a database attached to the website form?  Does it get stored in a Customer Relationship Management (CRM) application?  Does it get saved to a spreadsheet called Contacts?  In this real world example, we ultimately want the information in our CRM system, HubSpot.  How we get it there we’ll cover in the Connecting Data section below.  

‍

Lastly, let’s consider how this data needs to be organized.  In HubSpot there are Contacts (individuals) and Companies and an association exists between them.  This is just one way HubSpot helps an organization manage its data inventory.

‍

To recap, data is the raw material.  An organization needs to understand the data that is available, how it is organized, and where it is stored in order to use data effectively.  

‍

‍

Connecting Data

Managing your organization’s data inventory often requires connecting different processes or systems together.  Many think of this as simply data integration.  While data integration is a critical component of data management activities, there is a key requirement that must not be overlooked.  Building robust data quality throughout the data management cycles are absolutely critical to ensuring data is not only accurate but complete, timely, and reliable.  

‍

Going back to our website form.  Our website is hosted on a platform called Webflow.  Webflow forms have a pseudo database that underlie them so each form submission gets written to a table.  But remember we want the data in our CRM system so our various teams can utilize the data for various purposes.  We need to connect the systems and move the data from Webflow to HubSpot. 

‍

Luckily, Webflow has developed a connector that provides seamless integration with HubSpot.  Customers can exchange data between the Webflow “warehouse” and the HubSpot “warehouse” freely and easily.  We use built-in connector functionality to add records into our HubSpot Contacts instantly whenever a form is submitted ensuring that our warehouse is always fully stocked.  

‍

While we are talking about integration, let’s take a moment to consider the quality of the data we are likely to get with a submission.  How many of us have completed a form and used a throwaway email?  Maybe we leave certain fields blank because we don’t think they are relevant.  It’s fair to assume that the data could be less robust than we would like.  This is where data governance and data quality processes can alleviate those risks.

‍

Data governance allows us to define the people, processes, and technologies that can ensure a robust data management process.  In this case, we can use technology to enforce a process to aid in our data quality, namely making certain fields such as name and company required on the form that we need in order to support our use of the data.  

‍

But governance is not enough, we still have potential data quality issues and need to ensure that people, processes, and technologies are leveraged effectively to ensure data can be used reliably to make important business decisions.  In this, consider the email address.  Simply making it required is data governance.  Adding a validation to prevent submissions with email addresses from general email providers such as gmail, yahoo, or outlook is a data quality measure that improves the completeness and usefulness of the data.  

‍

Data integration can be achieved without data governance or data quality; however, to effectively connect systems and exchange accurate, complete, timely, and reliable data demands that these concepts be applied in concert with one another.

‍

‍

Care & Feeding

Unfortunately, data management is sometimes an afterthought in the business application universe owing to its complexity and less overtly end user facing nature.  End users fail to see the value until something goes wrong.  It’s a lot like the plumbing in your home, when it doesn’t work properly there’s an urgent problem to address.  Designing effective data management requires not only ensuring that data is accurate, complete, timely, and reliable but also resilient.  Security and ongoing maintenance are important activities.  

‍

Security is obvious, we don’t want data accessed by someone that is not entitled to the information - both external to the organization and internal.  Data security is a key foundational element of data management and it is important to realize that it extends beyond data integration.  Data security must be considered when designing data governance policies and procedures, when designing and building data integration and data quality processes, and most importantly when using the data.  Enterprise business applications must apply robust security models to ensure that valuable data is protected.  

‍

Organizations should also recognize that data management requires occasional maintenance.  In the world of SaaS, applications are constantly evolving as is your business.  Taking the time to reevaluate your data management practices ensures that your data will evolve with your business.  Understand how new functionality could improve your processes.  Evaluate if any changes could be negatively impacting your data management processes and adjust accordingly.  

‍

To close the loop on our website example, form data is stored in both Webflow and HubSpot.  Both applications are secured with single sign on and multifactor authentication.  Annually the HubSpot contact database is reviewed to purge any superfluous entries as well as update for known personnel changes.  During this review data is purged from Webflow since HubSpot is the customer system of record.  Off cycle, user requests to be forgotten are processed within the statutory requirement.  

‍

Data management, like any business process, is never complete.  Organizations should always review and evolve to ensure that their data is accurate, complete, timely, and reliable.  

‍

‍

Summary

I think ChatGPT summarized the value of data management pretty well:

‍

Effective data management is crucial for organizations to derive meaningful insights, make informed decisions, and maintain competitive advantages in today's data-driven world.

‍‍

We hope this article enabled a better understanding of what data management means for today’s organizations and encouraged you to consider how well your existing processes serve your data management needs.  

‍

If you would like to discuss your organization’s data management processes then head over to our Contact Us page and fill out the form - especially now that you know how our data management process works.  We’d love to connect with you.