Tag Archives: Informatica data quality

Don’t Take the Easy Way Out – Be a Data Quality Hero

When I talk to customers about dealing with poor data quality, I consistently hear something like, “We know we have data quality problems, but we can’t get the business to help take ownership and do something about it.” I think that this is taking the easy way out. Throwing your hands up in the air doesn’t make change happen – it only prolongs the pain. If you want to affect a positive change in data quality and are looking for ways to engage the business, then you should join Barbara Latulippe, Director of Enterprise Information Management for EMC and and Kristen Kokie, VP IT Enterprise Strategic Services for Informatica for our webinar on Thursday October 24th to hear how they have dealt with data quality in their combined 40+ years in IT.

Now, understandably, tackling data quality problems is no small undertaking, and it isn’t easy. In many instances, the reason why organizations choose to do nothing about data quality is that bad data has been present for so long that manual work around efforts have become ingrained in the business processes for consuming data. In these cases, changing the way people do things becomes the largest obstacle to dealing with the root cause of the issues. But that is also where you will be able to find the costs associated with bad data: lost productivity, ineffective decision making, missed opportunities, etc..

As discussed in this previous webinar,(link to replay on the bottom of the page), successfully dealing with poor data quality takes initiative, and it takes communication. IT Departments are the engineers of the business: they are the ones who understand process and workflows; they are the ones who build the integration paths between the applications and systems. Even if they don’t own the data, they do end up owning the data driven business processes that consume data. As such, IT is uniquely positioned to provide customized suggestions based off of the insight from multiple previous interactions with the data.

Bring facts to the table when talking to the business. As those who directly interact daily with data, IT is in position to measure and monitor data quality, to identify key data quality metrics; data quality scorecards and dashboards can shine a light on bad data and directly relate it to the business via the downstream workflows and business processes. Armed with hard facts about impact on specific business processes, a Business user has an easier time affixing a dollar value on the impact of that bad data. Here’s some helpful resources where you can start to build your case for improved data quality. With these tools and insight, IT can start to affect change.

Data is becoming the lifeblood of organizations and IT organizations have a huge opportunity to get closer to the business by really knowing the data of the business. While data quality invariably involves technological intervention, it is more so a process and change management issue that ends up being critical to success. The easier it is to tie bad data to specific business processes, the more constructive the conversation can be with the Business.

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Posted in Business/IT Collaboration, Data Governance, Data Integration, Data Quality, Pervasive Data Quality, Scorecarding, Uncategorized | Tagged , , , , | Leave a comment

Retail Case Study: Printemps Department Store Builds a Trusted Customer Data Foundation with MDM and Data Quality

If you have never traveled to France, you have missed the unique and exciting shopping experience offered at Printemps, a luxury fashion retailer. Its flagship store in Paris drives 60% of the company’s revenue. More than 1.5 million customers who love fashion visit this store as well as the retailer’s 15 other high-end stores around the country.

Printemps Haussmann, flagship department store in Paris, France.

Printemps’ goal is to cultivate long-term personal relationships with their high value customers by delivering exceptional services. Their strategy to accomplish this goal is to continuously meet their high value customers’ needs and expectations and create compelling incentives for customers to visit their stores.

Printemps’ marketing team is continually striving to be more customer-centric and improve campaign effectiveness. They are using customer analytics to segment their customers and better understand their preferences. For example:

  • Which customers prefer fashion, beauty or accessories?
  • Which customers prefer communications through the mail, email, mobile phone, social media channels?

Printemps has plenty of information about their 1.5 million customers. So what
was standing in their way? They lacked a 360-degree view of their high value
customers. The key culprit was duplicate customer information across multiple
systems.

I had the honor of introducing Olivier de Compiègne, who is responsible for Project Services and Customer Relationships at Printemps at Informatica World. Olivier’s main message: if your goal is to attract high value customers and boost customer loyalty, first you must invest in a solid customer data foundation.

To build their solid customer data foundation, Printemps’ team is leveraging Informatica Data Quality to ensure their customer information is as accurate and complete as possible across all key sources. They are using Informatica MDM, master data management (MDM) technology to rationalize customer information from numerous data sources to create a single customer view as well as a 360-degree customer view, which includes each customer’s purchase history.

Printemps’ solid customer data foundation is maintained on an ongoing basis, which allows Printemps’ marketing team to have confidence in the data they use for customer analytics and campaign management. Now they can truly support personalized relationships with customers and optimize their marketing by sending tailored messages to targeted customer segments.

If you are trying to cultivate long-term personal relationships with your customers and lack a 360 degree customer view, I hope Olivier’s story was helpful.  Do you have similiar goals? Please share your thoughts. I’m interested in hearing from you.

If you want to learn more about how Printemps’ is using Informatica Data Quality and Informatica MDM, please:

 

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Posted in Customer Acquisition & Retention, Data Quality, Master Data Management, Retail | Tagged , , , , , , , , , , , , , , , | Leave a comment

MDM – What’s The Cost Of Bad Data In Financial Services?

One of the most critical first steps for financial services firms looking to implement multidomain master data management (MDM) is to quantify the cost savings they could achieve.

Unfortunately, a thorough analysis of potential ROI is also one of the steps least followed (a key culprit being disconnects between business and IT).

This shortcoming is spotlighted in a new Informatica white paper, “Five Steps to Managing Reference Data More Effectively in Investment Banking,” which outlines key questions to ask in sizing up the cost implications of bad data and antiquated systems, such as:

  • How long does it take to introduce a new security to trade?
  • How many settlements need to be fixed manually?
  • How many redundant data feeds does your firm have to manage?
  • How accurate and complete are your end-of-day reports?
  • Do you have the data you need to minimize risk and exposure? (more…)
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Posted in Enterprise Data Management, Financial Services, Governance, Risk and Compliance, Master Data Management, Operational Efficiency | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment