Posts about MDM strategy

Data management during mergers are a challenge to CIOs and IT leaders. They have to manage a doubled IT infrastructure and merge product data into a single product classification system.

Merging product data is important to reap the benefits of a business merger, including brand consistency, better customer experiences and operational efficiency.

Read More

---

Using DaaS to make master data easily accessible to high-volume, data-consuming applications can drive significant competitive advantage.  

If you’re like most companies, you have several digital enablement projects underway to improve operational agility or enhance the customer experience in some way. For these initiatives to be a success, real-time access to business-critical master data is essential.  

Read More

---

With NRF 2022 complete, one thing is clear: change continues to be the new normal for the retail industry.

As industry leaders trekked back to New York to attend NRF 2022, attendees couldn’t help but notice that while things looked similar, much had changed. Since the last in-person NRF in 2020, while the world and various aspects of the global economy have shut down at various points, the retail industry kept going at an accelerated pace.

Photo credit: National Retail Federation

Read More

---

When it comes to data governance, the first considerations should be the company, its organizational structure, processes and the responsibilities that need to be defined before the right software can be deployed.

This is mirrored in the five most common reasons of failing data governance initiatives:

1. Too much at once (or too little)
2. Lack of support from management
3. Lack of communication and change management
4. Unclear goals
5. Focus on tools, not processes

Read More

---

Data silos are a huge problem for your ability to collaborate, operate efficiently and deliver excellent customer experiences. However, multidomain master data management (MDM) can bring your data silos together and create new zones of insight.

This article will explore the relationship between product and supplier master data domains.

Read More

---

To make money from data requires insightful data.

Data monetization is generally understood as the “process of using data to obtain quantifiable economic benefit” (Gartner Glossary, Data Monetization). Three typical ways to achieve this, include:

• Using data to make better decisions and thus enhance your business performance
• Sharing data with business partners for mutual benefit
• Selling data as a product or service

Read More

---

What the foundation of your Master Data Management (MDM) system is built on will depend on the implementation style you agree gives you the best chance of project success. And this will largely be determined by your business situation when it comes to data management.

There are a few different implementation styles to choose from with the main differences being whether you control your data from a central hub or synchronise the hub with your existing data sources.

Read More

---

Your master data management roadmap should be embedded in an overall master data management strategy methodology.

There's no one-size-fits all. A suggested methodology for a master data management strategy and data governance initiatives typically include the following five phases:

1. Education
2. Readiness assessment
3. Strategic roadmap
4. Master data management software selection
5. Business case

Read More

---

High-quality master data and transparent processes are necessary to protect and grow your business. Master data governance helps you achieve it.

Transparency and high-quality master data are essential to everything related to your business: revenue growth, operational efficiency, risk management and compliance, analytics and digital transformation; and your ability to control costs and be agile.

The following discusses what master data governance is, why you need it, and how to implement it.

Read More

---

Not all “multidomain” master data management (MDM) solutions are the same. Here are the differences and why you need to know.

When selecting solutions to help support your master data management and data governance ambitions, one of the many aspects you are likely to evaluate will be support for “multidomain” MDM. Your initial inclination is almost certain to be selecting a solution that can “do-it-all.” In many cases, this will be despite the fact you currently have a business use case for only one data domain; customer or product data, for example. A single solution that could do more in the future would, of course, be desirable, to make more efficient use of available resources.

Read More

---