Tag Archives: Master Data Management

Is the Internet of Things relevant for the government?

Get connected. Be connected. Make connections. Find connections. The Internet of Things (IoT) is all about connecting people, processes, data and, as the name suggests, things. The recent social media frenzy surrounding the ALS Ice Bucket Challenge has certainly reminded everyone of the power of social media, the Internet and a willingness to answer a challenge. Fueled by personal and professional connections, the craze has transformed fund raising for at least one charity. Similarly, IoT may potentially be transformational to the business of the public sector, should government step up to the challenge.

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Is the Internet of Things relevant for the government?

Government is struggling with the concept and reality of how IoT really relates to the business of government, and perhaps rightfully so. For commercial enterprises, IoT is far more tangible and simply more fun. Gaming, televisions, watches, Google glasses, smartphones and tablets are all about delivering over-the-top, new and exciting consumer experiences. Industry is delivering transformational innovations, which are connecting people to places, data and other people at a record pace.

It’s time to accept the challenge. Government agencies need to keep pace with their commercial counterparts and harness the power of the Internet of Things. The end game is not to deliver new, faster, smaller, cooler electronics; the end game is to create solutions that let devices connecting to the Internet interact and share data, regardless of their location, manufacturer or format and make or find connections that may have been previously undetectable. For some, this concept is as foreign or scary as pouring ice water over their heads. For others, the new opportunity to transform policy, service delivery, leadership, legislation and regulation is fueling a transformation in government. And it starts with one connection.

One way to start could be linking previously siloed systems together or creating a golden record of all citizen interactions through a Master Data Management (MDM) initiative. It could start with a big data and analytics project to determine and mitigate risk factors in education or linking sensor data across multiple networks to increase intelligence about potential hacking or breaches. Agencies could stop waste, fraud and abuse before it happens by linking critical payment, procurement and geospatial data together in real time.

This is the Internet of Things for government. This is the challenge. This is transformation.

This article was originally published on www.federaltimes.com. Please view the original listing here

 

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Posted in Big Data, Business Impact / Benefits, Data Integration, Data Security, Master Data Management, Public Sector, Uncategorized | Tagged , , , , , | Leave a comment

The Information Difference Pegs Informatica as a Top MDM Vendor

Information Difference MDM Diagram v2This blog post feels a little bit like bragging… and OK, I guess it is pretty self-congratulatory to announce that this year, Informatica was again chosen as a leader in MDM and PIM by The Information Difference. As you may know, The Information Difference is an independent research firm that specializes in the MDM industry and each year surveys, analyzes and ranks MDM and PIM providers and customers around the world. This year, like last year, The Information Difference named Informatica tops in the space.

Why do I feel especially chuffed about this?  Because of our customers.

(more…)

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Posted in Data Governance, Data Quality, Enterprise Data Management, Master Data Management | Tagged , , , , , , | Leave a comment

How Much is Poorly Managed Supplier Information Costing Your Business?

Supplier Information“Inaccurate, inconsistent and disconnected supplier information prohibits us from doing accurate supplier spend analysis, leveraging discounts, comparing and choosing the best prices, and enforcing corporate standards.”

This is quotation from a manufacturing company executive. It illustrates the negative impact that poorly managed supplier information can have on a company’s ability to cut costs and achieve revenue targets.

Many supply chain and procurement teams at large companies struggle to see the total relationship they have with suppliers across product lines, business units and regions. Why? Supplier information is scattered across dozens or hundreds of Enterprise Resource Planning (ERP) and Accounts Payable (AP) applications. Too much valuable time is spent manually reconciling inaccurate, inconsistent and disconnected supplier information in an effort to see the big picture. All this manual effort results in back office administrative costs that are higher than they should be.

Do these quotations from supply chain leaders and their teams sound familiar?

  • “We have 500,000 suppliers. 15-20% of our supplier records are duplicates. 5% are inaccurate.”
  • I get 100 e-mails a day questioning which supplier to use.”
  • “To consolidate vendor reporting for a single supplier between divisions is really just a guess.”
  • “Every year 1099 tax mailings get returned to us because of invalid addresses, and we play a lot of Schedule B fines to the IRS.”
  • “Two years ago we spent a significant amount of time and money cleansing supplier data. Now we are back where we started.”
Webinar, Supercharge Your Supply Chain Apps with Better Supplier Information

Join us for a Webinar to find out how to supercharge your supply chain applications with clean, consistent and connected supplier information

Please join me and Naveen Sharma, Director of the Master Data Management (MDM) Practice at Cognizant for a Webinar, Supercharge Your Supply Chain Applications with Better Supplier Information, on Tuesday, July 29th at 11 am PT.

During the Webinar, we’ll explain how better managing supplier information can help you achieve the following goals:

  1. Accelerate supplier onboarding
  2. Mitiate the risk of supply disruption
  3. Better manage supplier performance
  4. Streamline billing and payment processes
  5. Improve supplier relationship management and collaboration
  6. Make it easier to evaluate non-compliance with Service Level Agreements (SLAs)
  7. Decrease costs by negotiating favorable payment terms and SLAs

I hope you can join us for this upcoming Webinar!

 

 

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Posted in Business Impact / Benefits, Business/IT Collaboration, Data Integration, Data Quality, Manufacturing, Master Data Management | Tagged , , , , , , , , , , , , , , | Leave a comment

Master Data and Data Security …It’s Not Complicated

Master Data and Data Security…It’s Not Complicated

Master Data and Data Security…It’s Not Complicated

The statement on Master Data and Data security was well intended.  I can certainly understand the angst around data security.  Especially after Target’s data breach, it is top of mind for all IT and now business executives.  But the root of the statement was flawed.  And it got me thinking about master data and data security.

“If I use master data technology to create a 360-degree view of my client and I have a data breach, then someone could steal all the information about my client.”

Um, wait, what?  Insurance companies take personally identifiable information very seriously.  The statement is flawed in the relationship between client master data and securing your client data.  Let’s dissect the statement and see what master data and data security really mean for insurers.  We’ll start by level setting a few concepts.

What is your Master Client Record?

Your master client record is your 360-degree view of your client.  It represents everything about your client.  It uses Master Data Management technology to virtually integrate and syndicate all of that data into a single view.  It leverages identifiers to ensure integrity in the view of the client record.  And finally it makes an effort through identifiers to correlate client records for a network effect.

There are benefits to understanding everything about your client.  The shape and view of each client is specific to your business.  As an insurer looks at their policyholders, the view of “client” is based on relationships and context that the client has to the insurer.  This are policies, claims, family relationships, history of activities and relationships with agency channels.

And what about security?

Naturally there is private data in a client record.  But there is nothing about the consolidated client record that contains any more or less personally identifiable information.  In fact, most of the data that a malicious party would be searching for can likely be found in just a handful of database locations.  Additionally breaches happen “on the wire”.  Policy numbers, credit card info, social security numbers, and birth dates can be found in less than five database tables.  And they can be found without a whole lot of intelligence or analysis.

That data should be secured.  That means that the data should be encrypted or masked so that any breach will protect the data.  Informatica’s data masking technology allows this data to be secured in whatever location.  It provides access control so that only the right people and applications can see the data in an unsecured format.  You could even go so far as to secure ALL of your client record data fields.  That’s a business and application choice.  Do not confuse field or database level security with a decision to NOT assemble your golden policyholder record.

What to worry about?  And what not to worry about?

Do not succumb to fear of mastering your policyholder data.  Master Data Management technology can provide a 360-degree view.  But it is only meaningful within your enterprise and applications.  The view of “client” is very contextual and coupled with your business practices, products and workflows.  Even if someone breaches your defenses and grabs data, they’re looking for the simple PII and financial data.  Then they’re grabbing it and getting out. If the attacker could see your 360-degree view of a client, they wouldn’t understand it.  So don’t over complicate the security of your golden policyholder record.  As long as you have secured the necessary data elements, you’re good to go.  The business opportunity cost of NOT mastering your policyholder data far outweighs any imagined risk to PII breach.

So what does your Master Policyholder Data allow you to do?

Imagine knowing more about your policyholders.  Let that soak in for a bit.  It feels good to think that you can make it happen.  And you can do it.  For an insurer, Master Data Management provides powerful opportunities across everything from sales, marketing, product development, claims and agency engagement.  Each channel and activity has discreet ROI.  It also has direct line impact on revenue, policyholder satisfaction and market share.  Let’s look at just a few very real examples that insurers are attempting to tackle today.

  1. For a policyholder of a certain demographic with an auto and home policy, what is the next product my agent should discuss?
  2. How many people live in a certain policyholder’s household?  Are there any upcoming teenage drivers?
  3. Does this personal lines policyholder own a small business?  Are they a candidate for a business packaged policy?
  4. What is your policyholder claims history?  What about prior carriers and network of suppliers?
  5. How many touch points have your agents and had with your policyholders?  Were they meaningful?
  6. How can you connect with you policyholders in social media settings and make an impact?
  7. What is your policyholder mobility usage and what are they doing online that might interest your Marketing team?

These are just some of the examples of very streamlined connections that you can make with your policyholders once you have your 360-degree view. Imagine the heavy lifting required to do these things without a Master Policyholder record.

Fear is the enemy of innovation.  In mastering policyholder data it is important to have two distinct work streams.  First, secure the necessary data elements using data masking technology.  Once that is secure, gain understanding through the mastering of your policyholder record.  Only then will you truly be able to take your clients’ experience to the next level.  When that happens watch your revenue grow in leaps and bounds.

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Posted in Data Security, Financial Services, Master Data Management | Tagged , , | Leave a comment

Don’t Rely on CRM as Your Single Source of Trusted Customer Data

Step 1: Determine if you have a customer data problem

A statement I often hear from marketing and sales leaders unfamiliar with the concept of mastering customer data is, “My CRM application is our single source of trusted customer data.” They use CRM to onboard new customers, collecting addresses, phone numbers and email addresses. They append a DUNS number. So it’s no surprise they may expect they can master their customer data in CRM. (To learn more about the basics of managing trusted customer data, read this: How much does bad data cost your business?)

It may seem logical to expect your CRM investment to be your customer master – especially since so many CRM vendors promise a “360 degree view of your customer.” But you should only consider your CRM system as the source of truth for trusted customer data if:

Shopper
For most large enterprises, CRM never delivered on that promise of a trusted 360-degree customer view.

 ·  You have only a single instance of Salesforce.com, Siebel CRM, or other CRM

·  You have only one sales organization (vs. distributed across regions and LOBs)

·  Your CRM manages all customer-focused processes and interactions (marketing, service, support, order management, self-service, etc)

·  The master customer data in your CRM is clean, complete, fresh, and free of duplicates


Unfortunately most mid-to-large companies cannot claim such simple operations. For most large enterprises, CRM never delivered on that promise of a trusted 360-degree customer view. That’s what prompted Gartner analysts Bill O’Kane and Kimbery Collins to write this report,
 MDM is Critical to CRM Optimization, in February 2014.

“The reality is that the vast majority of the Fortune 2000 companies we talk to are complex,” says Christopher Dwight, who leads a team of master data management (MDM) and product information management (PIM) sales specialists for Informatica. Christopher and team spend each day working with retailers, distributors and CPG companies to help them get more value from their customer, product and supplier data. “Business-critical customer data doesn’t live in one place. There’s no clear and simple source. Functional organizations, processes, and systems landscapes are much more complicated. Typically they have multiple selling organizations across business units or regions.”

As an example, listed below are typical functional organizations, and common customer master data-dependent applications they rely upon, to support the lead-to-cash process within a typical enterprise:

·  Marketing: marketing automation, campaign management and customer analytics systems.
·  Ecommerce: e-commerce storefront and commerce applications.
·  Sales: sales force automation, quote management,
·  Fulfillment: ERP, shipping and logistics systems.
·  Finance: order management and billing systems.
·  Customer Service: CRM, IVR and case management systems.

The fragmentation of critical customer data across multiple organizations and applications is further exacerbated by the explosive adoption of Cloud applications such as Salesforce.com and Marketo. Merger and acquisition (M&A) activity is common among many larger organizations where additional legacy customer applications must be onboarded and reconciled. Suddenly your customer data challenge grows exponentially.  

Step 2: Measure how customer data fragmentation impacts your business

Ask yourself: if your customer data is inaccurate, inconstant and disconnected can you:

Customer data is fragmented across multiple applications used by business units, product lines, functions and regions.

Customer data is fragmented across multiple applications used by business units, product lines, functions and regions.

·  See the full picture of a customer’s relationship with the business across business units, product lines, channels and regions?  

·  Better understand and segment customers for personalized offers, improving lead conversion rates and boosting cross-sell and up-sell success?

·  Deliver an exceptional, differentiated customer experience?

·  Leverage rich sources of 3rd party data as well as big data such as social, mobile, sensors, etc.., to enrich customer insights?

“One company I recently spoke with was having a hard time creating a single consolidated invoice for each customer that included all the services purchased across business units,” says Dwight. “When they investigated, they were shocked to find that 80% of their consolidated invoices contained errors! The root cause was innaccurate, inconsistent and inconsistent customer data. This was a serious business problem costing the company a lot of money.”

Let’s do a quick test right now. Are any of these companies your customers: GE, Coke, Exxon, AT&T or HP? Do you know the legal company names for any of these organizations? Most people don’t. I’m willing to bet there are at least a handful of variations of these company names such as Coke, Coca-Cola, The Coca Cola Company, etc in your CRM application. Chances are there are dozens of variations in the numerous applications where business-critical customer data lives and these customer profiles are tied to transactions. That’s hard to clean up. You can’t just merge records because you need to maintain the transaction history and audit history. So you can’t clean up the customer data in this system and merge the duplicates.

The same holds true for B2C customers. In fact, I’m a nightmare for a large marketing organization. I get multiple offers and statements addressed to different versions of my name: Jakki Geiger, Jacqueline Geiger, Jackie Geiger and J. Geiger. But my personal favorite is when I get an offer from a company I do business with addressed to “Resident”. Why don’t they know I live here? They certainly know where to find me when they bill me!

Step 3: Transform how you view, manage and share customer data

Why do so many businesses that try to master customer data in CRM fail? Let’s be frank. CRM systems such as Salesforce.com and Siebel CRM were purpose built to support a specific set of business processes, and for the most part they do a great job. But they were never built with a focus on mastering customer data for the business beyond the scope of their own processes.

But perhaps you disagree with everything discussed so far. Or you’re a risk-taker and want to take on the challenge of bringing all master customer data that exists across the business into your CRM app. Be warned, you’ll likely encounter four major problems:

1) Your master customer data in each system has a different data model with different standards and requirements for capture and maintenance. Good luck reconciling them!

2) To be successful, your customer data must be clean and consistent across all your systems, which is rarely the case.

3) Even if you use DUNS numbers, some systems use the global DUNS number; others use a regional DUNS number. Some manage customer data at the legal entity level, others at the site level. How do you connect those?

4) If there are duplicate customer profiles in CRM tied to transactions, you can’t just merge the profiles because you need to maintain the transactional integrity and audit history. In this case, you’re dead on arrival.

There is a better way! Customer-centric, data-driven companies recognize these obstacles and they don’t rely on CRM as the single source of trusted customer data. Instead, they are transforming how they view, manage and share master customer data across the critical applications their businesses rely upon. They embrace master data management (MDM) best practices and technologies to reconcile, merge, share and govern business-critical customer data. 

More and more B2B and B2C companies are investing in MDM capabilities to manage customer households and multiple views of customer account hierarchies (e.g. a legal view can be shared with finance, a sales territory view can be shared with sales, or an industry view can be shared with a business unit).

 

Gartner Report, MDM is Critical to CRM Optimization, Bill O'Kane & Kimberly Collins, February 7 2014.

Gartner Report, MDM is Critical to CRM Optimization, Bill O’Kane & Kimberly Collins, February 7 2014.

According to Gartner analysts Bill O’Kane and Kimberly Collins, “Through 2017, CRM leaders who avoid MDM will derive erroneous results that annoy customers, resulting in a 25% reduction in potential revenue gains,” according to this Gartner report, MDM is Critical to CRM Optimization, February 2014.

Are you ready to reassess your assumptions about mastering customer data in CRM?

Get the Gartner report now: MDM is Critical to CRM Optimization.

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Posted in CMO, Customer Acquisition & Retention, Customers, Data Governance, Master Data Management, Mergers and Acquisitions | Tagged , , , , , , , , , , , , , , , , | Leave a comment

World Cup of Data: The Early Bird Closes the Sale

Did you know the 2014 Brasil World Cup is actually the World Cup of Data? In addition to the visible matches played on the pitch, eShops will be in a simultaneous struggle to win real-time online merchandise customers.

Let me explain. Jogi Löw, the manager of the German team, is known for his stylish attire. At every major event, each European Cup and World Cup, he wears newly designed shirts and suits. As a result, when television audiences see each new article of clothing, there is a corresponding increase in related online retail activity. When Löw began this tradition, people didn’t know that his outfits were made by Strenesse. As a result, people searched using the keywords “Jogi Löw Shirt.” This drove traffic to the eShop with the best search engine optimization, giving them more conversions and more revenue.

If a manager’s attire drives online retail sales, imagine how much demand there is for the jerseys worn by the most visible World Cup athletes? Many of the these players have huge social media followings. Consider the size of the social media followings of Ronaldo, Kakà, Neymar, Ronaldinho and Wayne Rooney:

football social top5

(Source: http://fanpagelist.com/category/athletes/soccer/view/list/sort/followers/page1)

There is huge demand for these player’s jerseys. This demand will only increase as the games progress. Once the winner is decided, Google searches will rise for phrases like “World Cup Winner Jersey 2014 of xxx”. Some refer to this as the super long tail. And research does show that search queries with 3 or more words have better conversion rates than queries with only 1 or 2 words.

Longtail-image

(Source: http://www.conductor.com/resource-center/research/long-tail-search )

Who can predict the winners?

What happens if a fairly unknown player scores the last goal in over time? How will that event impact social media activity and search engine volumes? Who will be able to leverage this activity to sell the relevant merchandising products fast enough? The eShop with the best data will have the quickest response. And the eShop with the quickest response will get the traffic and the revenue.

The world cup is a battle. The early bird closes the sale. It’s time to play the World Cup of Data.

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Posted in Master Data Management, PiM, Product Information Management, Real-Time, Retail | Tagged , , , , | Leave a comment

Who Has the Heart to Adopt this Orphan Oil Well?

As I browsed my BBC app a few weeks ago, I ran into this article about environmental contamination of oil wells in the UK, which were left to their own devices. The article explains that a lack of data and proper data management is causing major issues for gas and oil companies. In fact, researchers found no data for more than 2,000 inactive wells, many of which have been abandoned or “orphaned”(sealed and covered up). I started to scratch my head imagining what this problem looks like in places like Brazil, Nigeria, Malaysia, Angola and the Middle East. In these countries and regions, regulatory oversight is, on average, a bit less regulated.

Data Management

Like Oliver, this well needs a home!

On top of that, please excuse my cynicism here, but an “Orphan” well is just as ridiculous a concept as a “Dry” well.  A hole without liquid inside is not a well but – you guessed it – a hole.  Also, every well has a “Parent”, meaning

  • The person or company who drilled it
  • A  land owner who will get paid from its production and allowed the operation (otherwise it would be illegal)
  • A financier who fronted the equipment and research cost
  • A regulator, who is charged with overseeing the reservoir’s exploration

Let the “hydrocarbon family court judge” decide whose problem this orphan is with well founded information- no pun intended.  After all, this “domestic disturbance” is typically just as well documented as any police “house call”, when you hear screams from next door. Similarly, one would expect that when (exploratory) wells are abandoned and improperly capped or completed, there is a long track record about financial or operational troubles at the involved parties.  Apparently I was wrong.  Nobody seems to have a record of where the well actually was on the surface, let alone subsurface, to determine perforation risks in itself or from an actively managed bore nearby.

This reminds me of a meeting with an Asian NOC’s PMU IT staff, who vigorously disagreed with every other department on the reality on the ground versus at group level. The PMU folks insisted on having fixed all wells’ key attributes:

  1. Knowing how many wells and bores they had across the globe and all types of commercial models including joint ventures
  2. Where they were and are today
  3. What their technical characteristics were and currently are

The other departments, from finance to strategy, clearly indicated that 10,000 wells across the globe currently being “mastered” with (at least initially) cheap internal band aid fixes has a margin of error of up to 10%.   So much for long term TCO.  After reading this BBC article, this internal disagreement made even more sense.

If this chasm does not make a case for proper mastering of key operational entities, like wells, I don’t know what does. It also begs the question how any operation with potentially very negative long term effects can have no legally culpable party being capture in some sort of, dare I say, master register.  Isn’t this the sign of “rule of law” governing an advanced nation, e.g. having a land register, building permits, wills, etc.?

I rest my case, your honor.  May the garden ferries forgive us for spoiling their perfectly manicured lawn.  With more fracking and public scrutiny on the horizon, maybe regulators need to establish their own “trusted” well master file, rather than rely on oil firms’ data dumps.  After all, the next downhole location may be just a foot away from perforating one of these “orphans” setting your kitchen sink faucet on fire.

Do you think another push for local government to establish “well registries” like they did ten years ago for national IDs, is in order?

Disclaimer: Recommendations and illustrations contained in this post are estimates only and are based entirely upon information provided by the prospective customer and on our observations and benchmarks.  While we believe our recommendations and estimates to be sound, the degree of success achieved by the prospective customer is dependent upon a variety of factors, many of which are not under Informatica’s control and nothing in this post shall be relied upon as representative of the degree of success that may, in fact, be realized and no warranty or representation of success, either express or implied, is made.

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A Data-Driven Healthcare Culture is Foundational to Delivering Personalized Medicine in Healthcare

According to a recent article in the LA Times, healthcare costs in the United States far exceed costs in other countries. For example, heart bypass surgery costs an average of $75,345 in the U.S. compared to $15,742 in the Netherlands and $16,492 in Argentina. In the U.S. healthcare accounts for 18% of the U.S. GDP and is increasing. 

Michelle Blackmer is an healthcare industry expert at Informatica

Michelle Blackmer is an healthcare industry expert at Informatica

Michelle Blackmer is an healthcare industry expert at Informatica. In this interview, she explains why business as usual isn’t good enough anymore. Healthcare organizations are rethinking how they do business in an effort to improve outcomes, reduce costs, and comply with regulatory pressures such as the Affordable Care Act (ACA). Michelle believes a data-driven healthcare culture is foundational to personalized medicine and discusses the importance of clean, safe and connected data in executing a successful transformation.

Q. How is the healthcare industry responding to the rising costs of healthcare?
In response to the rising costs of healthcare, regulatory pressures (i.e. Affordable Care Act (ACA)), and the need to better patient outcomes at lower costs, the U.S. healthcare industry is transforming from a volume-based to a value-based model. In this new model, healthcare organizations need to invest in delivering personalized medicine.

To appreciate the potential of personalized medicine, think about your own healthcare experience. It’s typically reactive. You get sick, you go to the doctor, the doctor issues a prescription and you wait a couple of days to see if that drug works. If it doesn’t, you call the doctor and she tries another drug. This process is tedious, painful and costly.

Now imagine if you had a chronic disease like depression or cancer. On average, any given prescription drug only works for half of those who take it. Among cancer patients, the rate of ineffectiveness jumps to 75 percent. Anti-depressants are effective in only 62 percent of those who take them.

Video: MD Anderson Cancer CenterOrganizations like MD Anderson and UPMC aim to put an end to cancer. They are combining scientific research with access to clean, safe and connected data (data of all types including genomic data). The insights revealed will empower personalized chemotherapies. Personalized medicine offers customized treatments based on patient history and best practices. Personalized medicine will transform healthcare delivery. Click on the links to watch videos about their transformational work.

Q. What role does data play in enabling personalized medicine?
Data is foundational to value-based care and personalized medicine. Not just any data will do. It needs to be clean, safe and connected data. It needs to be delivered rapidly across hallways and across networks.

As an industry, healthcare is at a stage where meaningful electronic data is being generated. Now you need to ensure that the data is accessible and trustworthy so that it can be rapidly analyzed. As data is aggregated across the ecosystem, married with financial and genomic data, data quality issues become more obvious. It’s vital that you can define the data issues so the people can spend their time analyzing the data to gain insights instead of wading through and manually resolving data quality issues.

The ability to trust data will differentiate leaders from the followers. Leaders will advance personalized medicine because they rely on clean, safe and connected data to:

1)      Practice analytics as a core competency
2)      Define evidence, deliver best practice care and personalize medicine
3)      Engage patients and collaborate to foster strong, actionable relationships

Healthcare e-bookTake a look at this Healthcare eBook for more on this topic: Potential Unlocked: Transforming Healthcare by Putting Information to Work.

Q. What is holding healthcare organizations back from managing their healthcare data like other mission-critical assets?
When you say other mission-critical assets, I think of facilitates, equipment, etc. Each of these assets has people and money assigned to manage and maintain them. The healthcare organizations I talk to who are highly invested in personalized medicine recognize that data is mission-critical. They are investing in the people, processes and technology needed to ensure data is clean, safe and connected. The technology includes data integration, data quality and master data management (MDM).

What’s holding other healthcare organizations back is that while they realize they need data governance, they wrongly believe they need to hire big teams of “data stewards” to be successful. In reality, you don’t need to hire a big team. Use the people you already have doing data governance. You may not have made this a formal part of their job description and they might not have data governance technologies yet, but they do have the skillset and they are already doing the work of a data steward.

So while a technology investment is required and you need people who can use the technology, start by formalizing the data stewardship work people are doing already as part of their current job. This way you have people who understand the data, taking an active role in the management of the data and they even get excited about it because their work is being recognized. IT takes on the role of enabling these people instead of having responsibility for all things data.

Q. Can you share examples of how immature information governance is a serious impediment to healthcare payers and providers?
Cost of Bad DataSure, without information governance, data is not harmonized across sources and so it is hard to make sense of it. This isn’t a problem when you are one business unit or one department, but when you want to get a comprehensive view or a view that incorporates external sources of information, this approach falls apart.

For example, let’s say the cardiology department in a healthcare organization implements a dashboard. The dashboard looks impressive. Then a group of physicians sees the dashboard, point out erroes and ask where the information (i.e. diagnosis or attending physician) came from. If you can’t answer these questions, trace the data back to its sources, or if you have data inconsistencies, the dashboard loses credibility. This is an example of how analytics fail to gain adoption and fail to foster innovation.

Q. Can you share examples of what data-driven healthcare organizations are doing differently?
Certainly, while many are just getting started on their journey to becoming data-driven, I’m seeing some inspiring  examples, including:

  • Implementing data governance for healthcare analytics. The program and data is owned by the business and enabled by IT and supported by technology such as data integration, data quality and MDM.
  • Connecting information from across the entire healthcare ecosystem including 3rd party sources like payers, state agencies, and reference data like credit information from Equifax, firmographics from Dun & Bradstreet or NPI numbers from the national provider registry.
  • Establishing consistent data definitions and parameters
  • Thinking about the internet of things (IoT) and how to incorporate device data into analysis
  • Engaging patients through non-traditional channels including loyalty programs and social media; tracking this information in a customer relationship management (CRM) system
  • Fostering collaboration by understanding the relationships between patients, providers and the rest of the ecosystem
  • Analyzing data to understand what is working and what is not working so  that they can drive out unwanted variations in care

Q. What advice can you give healthcare provider and payer employees who want access to high quality healthcare data?
As with other organizational assets that deliver value—like buildings and equipment—data requires a foundational investment in people and systems to maximize return. In other words, institutions and individuals must start managing their mission-critical data with the same rigor they manage other mission-critical enterprise assets.

Q. Anything else you want to add?
Yes, I wanted to thank our 14 visionary customer executives at data-driven healthcare organizations such as MD Anderson, UPMC, Quest Diagnostics, Sutter Health, St. Joseph Health, Dallas Children’s Medical Center and Navinet for taking time out of their busy schedules to share their journeys toward becoming data-driven at Informatica World 2014.  In our next post, I’ll share some highlights about how they are using data, how they are ensuring it is clean, safe and connected and a few data management best practices. InformaticaWorld attendees will be able to download presentations starting today! If you missed InformaticaWorld 2014, stay tuned for our upcoming webinars featuring many of these examples.

 

 

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Posted in Business Impact / Benefits, Business/IT Collaboration, Customers, Data Governance, Data Integration, Data Quality, Enterprise Data Management, Healthcare, Informatica World 2014, Master Data Management, Vertical | Tagged , , , , , , , , , , , , , , | Leave a comment

Data-Powered Insights Fueled by the “Internet of Master Data”

Master data management (MDM) has come a long way in the past decade or so.  When I was supporting my company’s customer master implementation back in 2001, my management was thrilled to simply have a customer master that brought a bit of order to the chaos sharing customer data between our CRM and ERP applications and downstream into our marketing data warehouse.

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Fast forward to 2014 and mastering customer data alone is often table stakes for leadership trying to transform their business from a product- or account-centric to a customer-centric organizations.

Here at Informatica, we’ve seen over 75% of our MDM customers in the past year purchase for multidomain use cases – meaning the scope of their initiative often spans mastering data such as Customers, Suppliers and Products as part of a coordinated effort.  These organizations have built compelling business cases to demonstrate that mastering multiple domains – and the relationships among those domains – is necessary.  Only a true 360 degree view of relationships among any data can provide the necessary insights to deliver on the desired operational efficiencies, optimized customer experiences, and growth objectives for their companies.

The progress we’ve all made in multidomain MDM is impressive, but it’s just scratching the surface of what’s possible.  What happens when MDM meets Cloud, Social, the Internet of Things and other master data enrichment sources such as D&B and Acxiom?  Dennis Moore, Informatica’s GM and SVP for MDM, envisions that a new “Internet of Master Data” will be formed that can include a massive new set of sensor and social data which it leverages to infer and recommend a new class of relationship insights.   For example, in addition to sentiment and relationships from social networks, location data from mobile devices and sensors can now inform customer – and product – behaviors that span beyond direct transactions and interactions within your traditional business applications.

Those of you who have invested in building a foundation of clean, consistent and connected data have a huge advantage as the value of MDM grows exponentially with the exponential growth of data. You are well-positioned to take advantage of the deeper insights and potential innovations now possible by adding Cloud, Social, and Machine data to optimizing analytics and operations.

This week at Informatica World 2014 in Las Vegas, we kicked off with our fantastic MDM Day pre-conference event with over 500 attendees.  During the event, we shared some early insights into our MDM 10 release planned for later this year which integrates the Informatica Vibe engine and incorporates other elements of the just unveiled Informatica Intelligent Data Platform vision to make it easier for customers to gain a 360 degree view of their most critical business entities, including customers, suppliers, products and assets.

We continue to be inspired by our awesome MDM customers and partners, and we’re excited to see what they can do to harness the power of the Internet of Master Data!

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Posted in Informatica World 2014, Master Data Management, Vibe | Tagged , , , , | Leave a comment