Tag Archives: inconsistent data
30 MDM Customer Use Cases (Master Data Management in Action)
Master Data Management (MDM) has been used by companies for more than eight years to address the challenge of fragmented and inconsistent data across systems. Over the years we’ve compiled quite a cadre of uses cases across industries and strategic initiatives. I thought this outline of the 30 most common MDM initiatives may be of interest to those of you who are just getting started on your MDM journey. (more…)
Why MDM and Data Quality is Such a Big Deal for Big Data
Big Data is the confluence of three major technology trends hitting the industry right now: Big Transaction Data (describing the enormous growing volumes of transactional data within the enterprise), Big Interaction Data (describing new types of data such as Social Media data that are impacting the enterprise), and Big Data Processing (describing new ways of processing data such as Hadoop). If you can imagine companies having problems with business-critical master data such as customers, products, accounts, and locations at current data volumes, now that problem is compounded many-fold with the growth into Big Data. That’s where MDM and Data Quality come in as the fundamental solutions. So, why is MDM and Data Quality such a big deal for Big Data? (more…)
Are Line Of Business (LOB) Executives Involved In MDM Or Is It Mostly An IT Initiative?
In recent conversations, I’ve been asked whether line of business executives are getting involved in master data management (MDM), or whether MDM is still mostly an IT initiative.
Attract & Retain Customers with Informatica Customer Centricity Solution (with MDM at the core)
From our experience at Informatica, the business is absolutely involved! In fact, it’s often a high-impact business event that triggers the alarm that a company needs MDM and data quality to deliver trusted and complete data. Many times, the root cause of these business problems is inconsistent, incomplete and duplicated customer data. Two examples:
1) An $8 billion technology manufacturer implemented Informatica MDM after its IT team couldn’t quickly and accurately respond to an executive’s request for a list of the company’s top 400 B2B customers. It took IT six weeks to assemble the information because it was scattered across applications, and many large customers had complex hierarchies with multiple subsidiaries that all had to be reconciled by hand. Next step, focus on the next 400 customers. (more…)
Are You Building The Right Foundation For CRM 2.0? Bridge Your Data Silos With MDM
Improving your company’s ability to attract and retain customers requires that you take your customer relationship management (CRM) system to the next level of effectiveness—regardless of whether it’s a Software-as-a-Service (SaaS) application like salesforce.com or on-premise such as Siebel CRM or a custom-built application. (more…)
MDM-Embarking on CRM 2.0? Then You Know It’s All About The Data
Arguably the top lesson of CRM 1.0 was simply this—data matters. Though CRM 1.0 promised to deliver a 360-degree customer view, untold numbers of multimillion-dollar CRM systems fell short of expectations because they failed to address the incomplete, incorrect, inconsistent and duplicate data that proliferated across the enterprise.
Acquire & Retain Customers with Trusted & Complete Customer Data
Now companies are moving to CRM 2.0, in many cases to the cloud with salesforce.com or another software as a service (SaaS) provider. And this time, determined to get the data right, many businesses are looking to master data management (MDM) and data quality to generate a true 360-degree customer view. (more…)
MDM In Action: A New Demo On Customer Account & Channel Partner Management
One of the hottest areas of master data management (MDM) is using high quality master data to drive revenue by supporting sales and channel operations. Informatica customers have racked up some terrific successes using MDM to generate a single, reliable view of customer and account information—and here’s a key reason why.
Acquire & Retain Customers with Trusted & Complete Customer Data
With Informatica MDM and Informatica Data Quality, sales and channel personnel gain hands-on control of customer data, product data and channel partner data and the relationships between this data. Those customer-facing teams no longer need to spend most of their time hunting for information in the CRM system, SFA system, billing system, partner management and other systems and reconciling it in spreadsheets. And they don’t need to wait on IT to round up and deliver the data they need right away.
If you’re wondering how this works, check out our six-minute how-to demo on MDM for customer account and channel partner management. This new demo offers a practical, step-by-step walk-through of how a sales, marketing and channel operations personnel can evolve from trying to sort through the clutter of contradictory data from multiple systems to leveraging a single, actionable customer account data set that powers a 360-degree customer view in their CRM system so they can improve customer acquisition and retention.
How Banks Can Use MDM To Increase Customer Share of Wallet
If you mention master data management (MDM) to sales, marketing or customer service personnel in a bank, their eyes might glaze over. After all, MDM sounds like something for the IT folks to worry about—not something that can help customer-facing staff and managers do their jobs better.
Acquire & Retain Customers with Trusted & Complete Customer Data
But show them this new online demo on the business benefits of MDM, and you’d get a different reaction … quite possibly, “When can we have this up and running?”
This six-minute business-focused demo, Customer Centricity in Financial Services, gives you a step-by-step look at how sales, marketing and customer service in the banking industry can use Informatica MDM and Informatica Data Quality, to get a single view of each customer (also known as the single customer view), including which products and services they are using, and customer relationships (also known as house-holding). This information helps customer-facing employees improve customer acquisition and retention by identifying relevant cross-sell and up-sell opportunities to increase customer share of wallet, and by delivering better customer service because they have visibility into a customer’s full relationship with the bank. (And, it helps IT maximize the value of their customer relationship management (CRM) investment). This demo shows how easy it is to create three levels of customer views:
1) Single customer view: Creating golden records by reconciling names, addresses, emails, phone numbers, and other data from disparate sources for a single view of a customer.
2) 360-degree customer view: Expanding the single customer view to include the customer’s products across lines of business (checking, mortgage, IRA, car loan, etc.)
3) Extended customer view: Expanding the 360-degree customer view to reflect the customer’s network of people, business, and product relationships and help customer teams pursue long-term, multigenerational value. (more…)
Are You Shortchanging Your Customer-Facing Teams?
Are you giving your sales, marketing and service delivery teams the customer-centric views they need to excel?
Sure, you’ve rolled out sales force automation (SFA), customer relationship management (CRM), marketing automation, and other applications to support your their processes across your lines of business and regions… but that’s actually part of the problem. Those disparate systems usually contain inconsistent data, in various formats, on B2B customer accounts and their subsidiaries, divisions, locations and contacts, their products and service agreements as well as the sales reps and channel partners that are covering these accounts.
Because the data is sprawled out, often contradictory, and not readily accessible, your customer-facing teams are forced to spend valuable time stitching together spreadsheets with information from multiple systems. At many B2B companies, it’s not uncommon for sales reps to spend 70 percent of their time searching for and reconciling data—and just 30 percent on customer engagement. (more…)
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…)
The Win-Win Of Enabling Customer Centricity with MDM
One of the world’s largest financial services providers assessed the workload and productivity of its 16,000 financial advisors, and the results were not pretty. This Fortune 50 firm found that its customer-facing representatives were spending:
- 70% of their time searching for and reconciling data on customers and products
- 30% of their time on revenue-generating activities, such as cross-sell and up-sell
That’s a pretty poor ratio, and it hurt the bottom line with subpar productivity and lost revenue opportunities. Unfortunately, it’s not uncommon in financial services and other industries. And experience has shown that whatever you think your company’s ratio is, the reality is probably worse.
Attract and Retain Customers with Trusted and Complete Data
But it’s also a solvable problem, as you can find in our new white paper, “Get on the Fast Track to Maximizing Customer Value.”
For this financial services firm, the root cause of the problem was that business-critical data about customers, their products and services was spread across account-centric system silos, which prevented them from gaining a customer-centric view. Financial advisors were unable to readily identify which clients had which products. Without that insight, they couldn’t effectively cross-sell and up-sell the right products to the right customers. So they were forced to spend excessive time manually pulling information from all these separate systems into a spreadsheet.
To make matters worse, advisors couldn’t accurately measure each client’s value to the institution. The firm couldn’t tailor service levels to customer profitability, meaning that expensive services might be provided to customers of marginal profitability—while high-value customers didn’t receive the attention they deserved.