Posts about MDM strategy

Grocery is one of the retail sub channels that is poised to gain most from digital transformation.

The COVID-19 pandemic has permanently changed how we shop for groceries. Online grocers and fresh food delivery services are experiencing a rise in demand that can be hard to manage for those who are lagging digitally. Consumers expect expediency, transparency, and a seamless digital experience.

Your MDM roadmap should be embedded in an overall MDM strategy methodology.

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

1. Education
2. Readiness assessment
3. Strategic roadmap
4. MDM software selection
5. Business case

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.

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.

A primary growth vector on the mind of many CIOs today are mergers and acquisitions. And many of these CIOs are in charge of managing a host of internal systems that share data. Establishing a single source of truth that can unite these systems in near real-time, so that operations can run seamlessly across old and new business units alike, is a challenge all of these CIOs face.

Make sure MDM includes matching and linking, business rules, governance, data privacy, enrichment and consent management

If you’re evaluating master data management (MDM) solutions, what are the basic features it should offer and why? More importantly, how will each of these elements come together to benefit you and your organization? Following are six master data management tools and capabilities you should look for before selecting and investing in a solution for your organization.

In times of global, business and economic uncertainty – when data points are changing on an hourly basis and supply chain responsiveness and flexibility are more critical than ever – being able to trust your company’s data is paramount.

Communicating the value of MDM to executive leadership can be a challenge. Here are four simple steps to get started.

The return on investment (ROI) of master data management (MDM) is a topic that keeps captivating people – especially those considering investing in MDM. And with good reason. As with all major expenditures, people want to know what the outcome will be before they commit to it. It’s basic business logic.

Unfortunately, the answer isn’t always straightforward, since it isn’t necessarily easy to quantify the value of high-quality data and smoother data-driven business processes.

With this in mind, here are a few helpful steps to help you determine the ROI of a master data management implementation.

For CDOs, a centralized data strategy is to enable an enterprise to fully exploit data and analytics. To get to that point some essential capabilities are required.

• First, the enterprise must be able to identify, combine and manage multiple sources of data.
• Second, it must build the right analysis models for predicting and optimizing outcomes.
• Third, management must possess the will to transform the organization to understand how to leverage and convert the data and analytics models into decisions that improve business outcome.

In addition, certain prerequisites help clearly define the strategy for how to use data and analytics. The following offers 5 tips on how to do that.

In my previous blog post I explained master data management (MDM) and its importance in the context of the consumer and the customer experience. In this post, I look ahead and shed some light on what we can expect from a technology and customer experience perspective in the near future, as the growing expectations from consumers are currently driving businesses in new directions - and with that, they are also driving MDM.