Tag Archive for ‘MDM for customer data’

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We make ‘null’ mistakes

Published by Frano Bebseler on 09-01-2012 in Data Quality and Data Services. 0 Comments Tags: , , .

Wherever software is created, mistakes are being made. Software providers often presume their products are bug-free, but software of that kind doesn’t exist. Our departments works hard to prevent it, yet in our HIquality Life Cycle new bugs could still be introduced, even in the oldest modules that have been in use for over 25 years already. 

HIquality bug cycle

Usually our customers are satisfied with our product suite. At customer support I never receive information about the successful implementations. I got to know our software through the problems that occur, and in almost 15 years of acceptance testing and customer support, I’ve seen all kind of bugs passing by.
HIquality bug cycleSoftware crashes and never ending loops are nasty. Worse are those bugs that are not that visible in the beginning, but keep on growing in the course of time.
Recently we caught such a bug in our longest existing product HIquality Identify. Continue reading ‘We make ‘null’ mistakes’

Know Your Customers – improving your Corporate Social Responsibility

Published by Winfried van Holland on 30-09-2011 in Data Governance. 0 Comments Tags: , , , , , , , , , .
It’s not only what you achieve, it’s also how you behave. Some small organizations can still behave somewhat undetected way to achieve successful results. For medium and large organizations that is not what governments and customers expect from them. Transparency on Corporate Social Responsibility (CSR) are key in this and therefore a significant number of countries agreed on these in, amongst others, the OECD Guidelines for Multinational Enterprises.

This week, the latest results have been presented in The Netherlands on Transparency in the Banking area. And although some institutions score really good, others really need to take it at least one mile further to get a good or even fair score.

We agree with the recommendations of the report that compliance regulations can help/force in being more transparent, e.g., the SEC in the USA is enforcing more detailed information than their Dutch peer, the AFM. And also for Basel II the financial institutions need to know who they are dealing with in the end. The phrase - in the end – makes it even more difficult for the CSR, because not only the ultimate legal entity is now needed, but additional details per region and per sector are required. Continue reading ‘Know Your Customers – improving your Corporate Social Responsibility’

The “miracle” of customer data integration

Published by Holger Wandt on 24-08-2009 in Data Quality and MDM for customer data. 0 Comments Tags: , , , , , .

mulitple view

The more a company knows about its customer’s wishes, needs and habits and the more that company is able to tailor its proposition accordingly, the greater the value it will eventually provide for its customers. We all know that there are countless examples where defective, fragmented, or just plain poor customer data cause unnecessary costs, decrease in revenue, employee dissatisfaction or frustation, damage of the corporate image and many other unsdesirable or painful consequences.

Customer data quality and integration problems impact every area of the value chain of organisations. Far too often companies have a multiple view of their customers. Customer Data Integration (or MDM for Customer Data) is the key to providing companies with a single view of their customer. Continue reading ‘The “miracle” of customer data integration’

How-to create the Golden Record

Published by Ramon de Noronha on 21-08-2009 in MDM for customer data. 2 Comments Tags: , , , , , .

puzzle

The term Golden Record is closely related to Customer Data Integration or MDM for Customer data. It refers to the “single truth” which has been created or calculated from all those duplicate customer records from different systems. This post is not about finding or tagging all those duplicate records. There all kinds of ways to find them using advanced statistical methods, fuzzy matching etc.

But what do you once you have found the duplicates. How do you create the best possible customer data out of all gathered elements? Continue reading ‘How-to create the Golden Record’

The view of experts on MDM for 2009

Published by Ramon de Noronha on 03-02-2009 in Data Quality. 1 Comment Tags: , , , , , , , , , .

Jeff Kelly, who is a News Editor at SearchDataManagement.com has asked four industry experts for their views and forecasts for 2009 regarding Master Data Management. He has asked Rob Karel (Forrester) who delivered a key-note on the Data Quality Summit 2008 of Human Inference, Bill Swanton (AMR Research), Aaron Zornes (MDM Institute) and Andrew White (Gartner). The full article can be found here. The four analysts have come up with 17 predictions in total, it is interesting to see how their views differ and some predictions even contradict themselves.

Continue reading ‘The view of experts on MDM for 2009’

The added value of an integrated customer view

Published by Emile van de Klok on 08-12-2008 in MDM for customer data. 0 Comments Tags: , , , , .
MDM Demo

The added value of an integrated customer view depends strongly on the quality of that integrated customer view. Every organization that is seriously planning to create a single customer view should ask itself the following question: “What determines the quality of my customer view and so the accompanying level of added value?”

Prior to answering this question we need to take one step back. Why does not every organization have a single customer view? The cause lies in the fact that many organizations have their customer data spread across multiple systems all facilitating separate business processes. Additionally customer data is often highly polluted, fragmented and incomplete.

Continue reading ‘The added value of an integrated customer view’