Every organization faces challenges with data structure at numerous stages of its growth. The areas that tend to feel tougher pressure are operations, customer success, sales, marketing and IT.

If your organization relies on IT to generate “business-as-usual” reports, this is one of the clear signs that your data needs attention. Revenue forecasts, expense reports, employee turnover, and many other reports should be easily generated by their respective business areas.

As your organization grows, there are other elements that put a strain on your data structure. We list below the seven business challenges solved by MDM implementations at our clients.

1. Regulatory Pressures

Privacy, data, and right-to-know regulations, among others, are constantly changing. In addition, there are different regulations across jurisdictions, like GDPR in Europe and the California Consumer Privacy Act. Responding to and complying with these evolving regulations is key to avoiding hefty fines.

The previous approach of companies keeping every bit of data now violates new and emerging data protection regulations.

The European Union’s GDPR promotes the Data Minimization Principle for data collection. “Personal data shall be adequate, relevant and limited to what is necessary for relation to the purposes for which they are processed.”

This is a seamlessly simple principle, but minimizing data can be an intimidating quest. An internal company directive should determine which information should be collected and kept, and for how long to keep it. Whilst identifying the minimum amount of personal data needed to fulfill the company promises.

New policies and system capabilities are required, supporting organizations to efficiently manage the day-to-day task of data minimization — without losing valuable information and while minimizing risks.

Managing consent management for multiple records of the same customer is very challenging, making it hard to identify if consent was granted or not. MDM helps organizations to comply with regulations by unifying customer data and keeping consent information consolidated.

Do you know how efficiently and effectively are data assets leveraged within your organization? Take our Data Maturity Assessment to find out.

2. The Cost of Big, Bad Data

Data volumes are rising exponentially. Technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) add huge volumes of data to enterprise systems.

Maintaining the quality of the data that drives decisions is a growing challenge. The costs of bad data can be single, large ticket items or several small issues which might add up to big amounts.

Read this case study to learn how we helped this $230 billion-dollar company by improving its data quality, delivering agile reports and supporting decision-making.

3. Missed Revenue & Opportunities

A Gartner prediction states that “By 2023, organizations embedding privacy user experience into the customer experience will enjoy greater trustworthiness and up to 20% more digital revenue than those that don’t.”

The better the master data, the more that information can be used for improving customer experience, working on forecasts, and opening new revenue streams.

4. Wasted Technology Investments

As the old saying goes, garbage-in-garbage-out. If your organization pursues new technology initiatives based on bad data, the results will likely be very limited.

Master Data Management can help remove those limitations by providing the best possible data in a timely fashion.

5. Wasted Marketing Budget

As the business area that broadly communicates with your existing and prospective customers, Marketing depends on quality data (among others) to perform its job well.

Printing, mailing and bad customer experience due to bad data can be extremely costly to organizations of all sizes, especially in the business-to-consumer space dealing with huge volumes of clients.

6. Improving Customer Experience

Modern lives are intertwined with data. We spend four hours a day on average on our smartphones, two-and-a-half hours on social media, and many more on video calls.

Experience and Insights teams have never had so much data to work with. Our data footprints are left in search queries, social media posts, and Uber journeys. Cell towers and satellites can track our physical movements. Customer surveys, web analytics, NPS scores, and CRM profiles add to the huge amounts of data.

We could be garnering better value from all this data if the sources weren’t disconnected from each other.

You have probably seen the term 360-degree view of the customer many times. There are many benefits to building this, but organizations face challenges to build it in a unified way.

One of the main challenges lies in bringing together data from disparate sources. A customer’s personal data, for example, might be stored in a CRM like Hubspot, their order history data might be in an old system, their purchase data might be in a POS system like Shopify and their social media data might be on LinkedIn, Facebook, Instagram or Twitter.

Our Business 360 Solutions provide you with more information on how to address this.

7. Mergers & Acquisitions

Mergers and acquisitions support the growth of many organizations, but also create a number of challenges – from branding and positioning to challenges with accessing and integrating the data from the incoming systems. These can dramatically slow down operations, customer success, sales and profits for the newly-formed organization.

A Master Data Management system implemented to best practices prevents the escalation of these challenges and creates efficiencies from the outset.

Contact us to learn more about our MDM solutions.