Category Archives: Customers
In my last blog, I talked about the dreadful experience of cleaning raw data by hand as a former analyst a few years back. Well, the truth is, I was not alone. At a recent data mining Meetup event in San Francisco bay area, I asked a few analysts: “How much time do you spend on cleaning your data at work?” “More than 80% of my time” and “most my days” said the analysts, and “they are not fun”.
But check this out: There are over a dozen Meetup groups focused on data science and data mining here in the bay area I live. Those groups put on events multiple times a month, with topics often around hot, emerging technologies such as machine learning, graph analysis, real-time analytics, new algorithm on analyzing social media data, and of course, anything Big Data. Cools BI tools, new programming models and algorithms for better analysis are a big draw to data practitioners these days.
That got me thinking… if what analysts said to me is true, i.e., they spent 80% of their time on data prepping and 1/4 of that time analyzing the data and visualizing the results, which BTW, “is actually fun”, quoting a data analyst, then why are they drawn to the events focused on discussing the tools that can only help them 20% of the time? Why wouldn’t they want to explore technologies that can help address the dreadful 80% of the data scrubbing task they complain about?
Having been there myself, I thought perhaps a little self-reflection would help answer the question.
As a student of math, I love data and am fascinated about good stories I can discover from them. My two-year math program in graduate school was primarily focused on learning how to build fabulous math models to simulate the real events, and use those formula to predict the future, or look for meaningful patterns.
I used BI and statistical analysis tools while at school, and continued to use them at work after I graduated. Those software were great in that they helped me get to the results and see what’s in my data, and I can develop conclusions and make recommendations based on those insights for my clients. Without BI and visualization tools, I would not have delivered any results.
That was fun and glamorous part of my job as an analyst, but when I was not creating nice charts and presentations to tell the stories in my data, I was spending time, great amount of time, sometimes up to the wee hours cleaning and verifying my data, I was convinced that was part of my job and I just had to suck it up.
It was only a few months ago that I stumbled upon data quality software – it happened when I joined Informatica. At first I thought they were talking to the wrong person when they started pitching me data quality solutions.
Turns out, the concept of data quality automation is a highly relevant and extremely intuitive subject to me, and for anyone who is dealing with data on the regular basis. Data quality software offers an automated process for data cleansing and is much faster and delivers more accurate results than manual process. To put that in math context, if a data quality tool can reduce the data cleansing effort from 80% to 40% (btw, this is hardly a random number, some of our customers have reported much better results), that means analysts can now free up 40% of their time from scrubbing data, and use that times to do the things they like – playing with data in BI tools, building new models or running more scenarios, producing different views of the data and discovering things they may not be able to before, and do all of that with clean, trusted data. No more bored to death experience, what they are left with are improved productivity, more accurate and consistent results, compelling stories about data, and most important, they can focus on doing the things they like! Not too shabby right?
I am excited about trying out the data quality tools we have here at Informtica, my fellow analysts, you should start looking into them also. And I will check back in soon with more stories to share..
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:
· 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:
· 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).
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.
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. 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.
Organizations 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
Take 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?
Sure, 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.
- A loss of customer trust
- Revenue shortfalls
- A plummeting stock price
- C-level executives losing their jobs
As a result, Data security and privacy has become a key topic of discussion, not just in IT meetings, but in the media and the boardroom.
Preventing access to sensitive data has become more complex than ever before. There are new potential entry points that IT never previously considered. These new options go beyond typical BYOD user devices like smartphones and tablets. Today’s entry points can be much smaller: Things like HVAC controllers, office polycoms and temperature control systems.
So what can organizations do to combat this increasing complexity? Traditional data security practices focus on securing both the perimeter and the endpoints. However, these practices are clearly no longer working and no longer manageable. Not only is the number and type of devices expanding, but the perimeter itself is no longer present. As companies increasingly outsource, off-shore and move operations to the cloud, it is no longer possible fence the perimeters and to keep intruders out. Because 3rd parties often require some form of access, even trusted user credentials may fall into the hands of malicious intruders.
Data security requires a new approach. It must use policies to follow the data and to protect it, regardless of where it is located and where it moves. Informatica is responding to this need. We are leveraging our market leadership and domain expertise in data management and security. We are defining a new data security offering and category. This week, we unveiled our entry into the Data Security market at our Informatica World conference. Our new security offering, Secure@Source™ will allow enterprises to discover, detect and protect sensitive data.
The first step towards protecting sensitive data is to locate and identify them. So Secure@Source™ first allows you discover where all the sensitive data are located in the enterprise and classify them. As part of the discovery, Secure@source also analyzes where sensitive data is being proliferated, who has access to the data, who are actually accessing them and whether the data is protected or unprotected when accessed. Secure@Source™ leverages Informatica’s PowerCenter repository and lineage technology to perform a first pass, quick discovery with a more in depth analysis and profiling over time. The solution allows you to determine the privacy risk index of your enterprise and slice and dice the analysis based on region, departments, organization hierarchy, as well as data classifications.
The longer term vision of Secure@Source™ will allow you to detect suspicious usage patterns and orchestrate the appropriate data protection method, such as: alerting, blocking, archiving and purging, dynamically masking, persistently masking, encrypting, and/or tokenizing the data. The data protection method will depend on whether the data store is a production or non-production system, and whether you would like to de-identify sensitive data across all users or only for some users. All can be deployed based on policies. Secure@Source™ is intended to be an open framework for aggregating data security analytics and will integrate with key partners to provide a comprehensive visibility and assessment of an enterprise data privacy risk.
Secure@Source™ is targeted for beta at the end of 2014 and general availability in early 2015. Informatica is recruiting a select group of charter customers to drive and provide feedback for the first release. Customers who are interested in being a charter customer should register and send email to SecureCustomers@informatica.com.
“Start your master data management (MDM) journey knowing how it will deliver a tangible business outcome. Will it help your business generate revenue or cut costs? Focus on the business value you plan to deliver with MDM and revisit it often,” advises Michael Delgado, Information Management Director at Citrix during his presentation at MDM Day, the InformaticaWorld 2014 pre-conference program. MDM Day focused on driving value from business-critical information and attracted 500 people.
In Ravi Shankar’s recent MDM Day preview blog, Part 2: All MDM, All Day at Pre-Conference Day at InformaticaWorld, he highlights the amazing line up of master data management (MDM) and product information management (PIM) customers speakers, Informatica experts as well as our talented partner sponsors.
Here are my MDM Day fun facts and key takeaways:
- Did you know that every 2 seconds an aircraft with GE engine technology is taking off somewhere in the world?
GE Aviation’s Chief Enterprise Architect, Ginny Walker, presented “Operationalizing Critical Business Processes: GE Aviation’s MDM Story.” GE Aviation is a $22 billion company and a leading provider of jet engines, systems and services. Ginny shared the company’s multi-year journey to improve installed-base asset data management. She explained how the combination of data, analytics, and connectivity results in productivity improvements such as reducing up to 2% of the annual fuel bill and reducing delays. The keys to GE Aviation’s analytical MDM success were: 1) tying MDM to business metrics, 2) starting with a narrow scope, and 3) data stewards. Ginny believes that MDM is an enabler for the Industrial Internet and Big Data because it empowers companies to get insights from multiple sources of data.
- Did you know that EMC has made a $17 billion investment in acquisitions and is integrating more than 70 technology companies?
EMC’s Barbara Latulippe, aka “The Data Diva,” is the Senior Director of Enterprise Information Management (EIM). EMC is a $21.7 billion company that has grown through acquisition and has 60,000 employees worldwide. In her presentation, “Formula for Success: EMC MDM Best Practices,” Barbara warns that if you don’t have a data governance program in place, you’re going to have a hard time getting an MDM initiative off the ground. She stressed the importance of building a data governance council and involving the business as early as possible to agree on key definitions such as “customer.” Barbara and her team focused on the financial impact of higher quality data to build a business case for operational MDM. She asked her business counterparts, “Imagine if you could onboard a customer in 3 minutes instead of 15 minutes?”
- Did you know that Citrix is enabling the mobile workforce by uniting apps, data and services on any device over any network and cloud?
Citrix’s Information Management Director, Michael Delgado, presented “Citrix MDM Case Study: From Partner 360 to Customer 360.” Citrix is a $2.9 billion Cloud software company that embarked on a multi-domain MDM and data governance journey for channel partner, hierarchy and customer data. Because 90% of the company’s product bookings are fulfilled by channel partners, Citrix started their MDM journey to better understand their total channel partner relationship to make it easier to do business with Citrix and boost revenue. Once they were successful with partner data, they turned to customer data. They wanted to boost customer experience by understanding the total customer relationship across products lines and regions. Armed with this information, Citrix employees can engage customers in one product renewal process for all products. MDM also helps Citrix’s sales team with white space analysis to identify opportunities to sell more user licenses in existing customer accounts.
- Did you know Quintiles helped develop or commercialize all of the top 5 best-selling drugs on the market?
Quintiles’ Director of the Infosario Data Factory, John Poonnen, presented “Using Multi-domain MDM to Gain Information Insights:How Quintiles Efficiently Manages Complex Clinical Trials.” Quintiles is the world’s largest provider of biopharmaceutical development and commercial outsourcing services with more than 27,000 employees. John explained how the company leverages a tailored, multi-domain MDM platform to gain a holistic view of business-critical entities such as investigators, research facilities, clinical studies, study sites and subjects to cut costs, improve quality, improve productivity and to meet regulatory and patient needs. “Although information needs to flow throughout the process – it tends to get stuck in different silos and must be manually manipulated to get meaningful insights,” said John. He believes master data is foundational — combining it with other data, capabilities and expertise makes it transformational.
While I couldn’t attend the PIM customer presentations below, I heard they were excellent. I look forward to watching the videos:
- Crestline/ Geiger: Dale Denham, CIO presented, “How Product Information in eCommerce improved Geiger’s Ability to Promote and Sell Promotional Products.”
- Murdoch’s Ranch and Home Supply: Director of Marketing, Kitch Walker presented, “Driving Omnichannel Customer Engagement – PIM Best Practices.”
I also had the opportunity to speak with some of our knowledgeable and experienced MDM Day partner sponsors. Go to Twitter and search for #MDM and #DataQuality to see their advice on what it takes to successfully kick-off and implement an MDM program.
There are more thought-provoking MDM and PIM customer presentations taking place this week at InformaticaWorld 2014. To join or follow the conversation, use #INFA14 #MDM or #INFA14 #PIM.
Bad data is bad for business. Ovum Research reported that poor quality data is costing businesses at least 30% of revenues. Never before have business leaders across a broad range of roles recognized the importance of using high quality information to drive business success. Leaders in functions ranging from marketing and sales to risk management and compliance have invested in world-class applications, six sigma processes, and the most advanced predictive analytics. So why are you not seeing more return on that investment? Simply put, if your business-critical data is a mess, the rest doesn’t matter.
Not all business leaders know there’s a better way to manage their business-critical data. So, I asked Dennis Moore, the senior vice president and general manager of Informatica’s MDM business, who clocked hundreds of thousands of airline miles last year visiting business leaders around the world, to talk about the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).
Q. Why are business leaders focusing on business-critical data now?
A. Leaders have always cared about their business-critical data, the master data on which their enterprises depend most — their customers, suppliers, the products they sell, the locations where they do business, the assets they manage, the employees who make the business perform. Leaders see the value of having a clear picture, or “best version of the truth,” describing these “master data” entities. But, this is hard to come by with competing priorities, mergers and acquisitions and siloed systems.
As companies grow, business leaders start realizing there is a huge gap between what they do know and what they should know about their customers, suppliers, products, assets and employees. Even worse, most businesses have lost their ability to understand the relationships between business-critical data so they can improve business outcomes. Line of business leaders have been asking questions such as:
- How can we optimize sales across channels when we don’t know which customers bought which products from which stores, sites or suppliers?
- How can we quickly execute a recall when we don’t know which supplier delivered a defective part to which factory and where those products are now?
- How can we accelerate time-to-market for a new drug, when we don’t know which researcher at which site used which combination of compounds on which patients?
- How can we meet regulatory reporting deadlines, when we don’t know which model of a product we manufactured in which lot on which date?
Q. What is the crux of the problem?
A. The crux of the problem is that as businesses grow, their business-critical data becomes fragmented. There is no big picture because it’s scattered across applications, including on premise applications (such as SAP, Oracle and PeopleSoft) and cloud applications (such as Salesforce, Marketo, and Workday). But it gets worse. Business-critical data changes all the time. For example,
- a customer moves, changes jobs, gets married, or changes their purchasing habits;
- a suppliers moves, goes bankrupt or acquires a competitor;
- you discontinue a product or launch a new one; or
- you onboard a new asset or retire an old one.
As all this change occurs, business-critical data becomes inconsistent, and no one knows which application has the most up-to-date information. This costs companies money. It saps productivity and forces people to do a lot of manual work outside their best-in-class processes and world-class applications. One question I always ask business leaders is, “Do you know how much bad data is costing your business?”
Q. What can business leaders do to deal with this issue?
A. First, find out where bad data is having the most significant impact on the business. It’s not hard – just about any employee can share stories of how bad data led to a lost sale, an extra “truck roll,” lost leverage with suppliers, or a customer service problem. From the call center to the annual board planning meeting, bad data results in sub-optimal decisions and lost opportunities. Work with your line of business partners to reach a common understanding of where an improvement can really make a difference. Bad master data is everywhere, but bad master data that has material costs to the business is a much more pressing and constrained problem. Don’t try to boil the ocean or bring a full-blown data governance maturity level 5 approach to your organization if it’s not already seeing success from better data!
Second, focus on the applications and processes used to create, share, and use master data. Many times, some training, a tweak to a process, or a new interface can be created between systems, resulting in very significant improvements for the users without major IT work or process changes.
Lastly, look for a technology that is purpose-built to deal with this problem. Master data management (MDM) helps companies better manage business-critical data in a central location on an ongoing basis and then share that “best version of the truth” with all on premise and cloud applications that need it.
Let’s use customer data as an example. If valuable customer data is located in applications such as Salesforce, Marketo, Seibel CRM, and SAP, MDM brings together all the business-critical data, the core that’s the same across all those applications, and creates the “best version of the truth.” It also creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.
MDM then shares that “mastered” customer data and the total customer relationship view with the applications that want it. MDM can be used to master the relationships between customers, such as legal entity hierarchies. This helps sales and customer service staff be more productive, while also improving legal compliance and management decision making. Advanced MDM products can also manage relationships across different types of master data. For example, advanced MDM enables you to relate an employee to a project to a contract to an asset to a commission plan. This ensures accurate and timely billing, effective expense management, managed supplier spend, and even improved workforce deployment.
When your sales team has the best possible customer information in Salesforce and the finance team has the best possible customer information in SAP, no one wastes time pulling together spreadsheets of information outside of their world-class applications. Your global workforce doesn’t waste time trying to investigate whether Jacqueline Geiger in one system and Jakki Geiger in another system is one or two customers, sending multiple bills and marketing offers at high cost in postage and customer satisfaction. All employees who have access to mastered customer information can be confident they have the best possible customer information available across the organization to do their jobs. And with the most advanced and intelligent data platform, all this information can be secured so only the authorized employees, partners, and systems have access.
Q. Which industries stand to gain the most from mastering their data?
A. In every industry there is some transformation going on that’s driving the need to know people, places and things better. Take insurance for example. Similar to the transformation in the travel industry that reduced the need for travel agents, the insurance industry is experiencing a shift from the agent/broker model to a more direct model. Traditional insurance companies now have an urgent need to know their customers so they can better serve them across all channels and across multiple lines of business.
In other industries, there is an urgent need to get a lot better at supply-chain management or to accelerate new product introductions to compete better with an emerging rival. Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data, particularly in industries undergoing rapid transformation, or with rapidly changing regulatory requirements.
Q. Which business functions seem most interested in mastering their business-critical data?
A. It varies by industry, but there are three common threads that seem to span most industries:
- MDM can help the marketing team optimize the cross-sell and up-sell process with high quality data about customers, their households or company hierarchies, the products and services they have purchased through various channels, and the interactions their organizations have had with these customers.
- MDM can help the procurement team optimize strategic sourcing including supplier spend management and supplier risk management with high quality data about suppliers, company hierarchies, contracts and the products they supply.
- MDM can help the compliance teams manage all the business-critical data they need to create regulatory reports on time without burning the midnight oil.
Q. How is the use of MDM evolving?
A. When MDM technology was first introduced a decade ago, it was used as a filter. It cleaned up business-critical data on its way to the data warehouse so you’d have clean, consistent, and connected information (“conformed dimensions”) for reporting. Now business leaders are investing in MDM technology to ensure that all of their global employees have access to high quality business-critical data across all applications. They believe high quality data is mission-critical to their operations. High quality data is viewed as the the lifeblood of the company and will enable the next frontier of innovation.
Second, many companies mastered data in only one or two domains (customer and product), and used separate MDM systems for each. One system was dedicated to mastering customer data. You may recall the term Customer Data Integration (CDI). Another system was dedicated to mastering product data. Because the two systems were in silos and business-critical data about customers and products wasn’t connected, they delivered limited business value. Since that time, business leaders have questioned this approach because business problems don’t contain themselves to one type of data, such as customer or product, and many of the benefits of mastering data come from mastering other domains including supplier, chart of accounts, employee and other master or reference data shared across systems.
The relationships between data matter to the business. Knowing what customer bought from which store or site is more valuable than just knowing your customer. The business insights you can gain from these relationships is limitless. Over 90% of our customers last year bought MDM because they wanted to master multiple types of data. Our customers value having all types of business-critical data in one system to deliver clean, consistent and connected data to their applications to fuel business success.
One last evolution we’re seeing a lot involves the types and numbers of systems connecting to the master data management system. In the past, there were a small number of operational systems pushing data through the MDM system into a data warehouse used for analytical purposes. Today, we have customers with hundreds of operational systems communicating with each other via an MDM system that has just a few milliseconds to respond, and which must maintain the highest levels of availability and reliability of any system in the enterprise. For example, one major retailer manages all customer information in the MDM system, using the master data to drive real-time recommendations as well as a level of customer service in every interaction that remains the envy of their industry.
Q. Dennis, why should business leaders consider attending MDM Day?
A. Business leaders should consider attending MDM Day at InformaticaWorld 2014 on Monday, May 12, 2014. You can hear first-hand the business value companies are gaining by using clean, consistent and connected information in their operations. We’re excited to have fantastic customers who are willing to share their stories and lessons learned. We have presenters from St. Jude Medical, Citrix, Quintiles and Crestline Geiger and panelists from Thomson Reuters, Accenture, EMC, Jones Lang Lasalle, Wipro, Deloitte, AutoTrader Group, McAfee-Intel, Abbvie, Infoverity, Capgemini, and Informatica among others.
Last year’s Las Vegas event, and the events we held in London, New York and Sao Paolo were extremely well received. This year’s event is packed with even more customer sessions and opportunities to learn and to influence our product road map. MDM Day is one day before InformaticaWorld and is included in the cost of your InformaticaWorld registration. We’d love to see you there!
See the MDM Day Agenda.
I love exploring new places. I’ve had exceptional experiences at the W in Hong Kong, El Dorado Royale in the Riviera Maya and Ventana Inn in Big Sur. I belong to almost every loyalty program under the sun, but not all hospitality companies are capitalizing on the potential of my customer information. Imagine if employees had access to it so they could personalize their interactions with me and send me marketing offers that appeal to my interests.
Do I have high expectations? Yes. But so do many travelers. This puts pressure on marketing and sales executives who want to compete to win. According to Deloitte’s report, “Hospitality 2015: Game changers or spectators?,” hospitality companies need to adapt to meet consumers’ increasing expectations to know their preferences and tastes and to customize packages that suit individual needs.
In this interview, Jeff Klagenberg, senior principal at Myers-Holum, explains how one of the largest, most customer-focused companies in the hospitality industry is investing in better customer, product, and asset information. Why? To personalize customer interactions, bundle appealing promotion packages and personalize marketing offers across channels.
Q: What are the company’s goals?
A: The executive team at one of the world’s leading providers of family travel and leisure experiences is focused on achieving excellence in quality and guest services. They generate revenues from the sales of room nights at hotels, food and beverages, merchandise, admissions and vacation club properties. The executive team believes their future success depends on stronger execution based on better measurement and a better understanding of customers.
Q: What role does customer, product and asset information play in achieving these goals?
A: Without the highest quality business-critical data, how can employees continually improve customer interactions? How can they bundle appealing promotional packages or personalize marketing offers? How can they accurately measure the impact of sales and marketing efforts? The team recognized the powerful role of high quality information in their pursuit of excellence.
Q: What are they doing to improve the quality of this business-critical information?
A: To get the most value out of their data and deliver the highest quality information to business and analytical applications, they knew they needed to invest in an integrated information management infrastructure to support their data governance process. Now they use the Informatica Total Customer Relationship Solution, which combines data integration, data quality, and master data management (MDM). It pulls together fragmented customer information, product information, and asset information scattered across hundreds of applications in their global operations into one central, trusted location where it can be managed and shared with analytical and operational applications on an ongoing basis.
Q: How will this impact marketing and sales?
A: With clean, consistent and connected customer information, product information, and asset information in the company’s applications, they are optimizing marketing, sales and customer service processes. They get limitless insights into who their customers are and their valuable relationships, including households, corporate hierarchies and influencer networks. They see which products and services customers have purchased in the past, their preferences and tastes. High quality information enables the marketing and sales team to personalize customer interactions across touch points, bundle appealing promotional packages, and personalize marketing offers across channels. They have a better understanding of which marketing, advertising and promotional programs work and which don’t.
Q: What is the role did the marketing and sales leaders play in this initiative?
A: The marketing leaders and sales leaders played a key role in getting this initiative off the ground. With an integrated information management infrastructure in place, they’ll benefit from better integration between business-critical master data about customers, products and assets and transaction data.
Q. How will this help them gain customer insights from “Big Data”?
A. We helped the business leaders understand that getting customer insights from “Big Data” such as weblogs, call logs, social and mobile data requires a strong backbone of integrated business-critical data. By investing in a data-centric approach, they future-proofed their business. They are ready to incorporate any type of data they will want to analyze, such as interaction data. A key realization was there is no such thing as “Small Data.” The future is about getting very bit of understanding out of every data source.
Q: What advice do you have for hospitality industry executives?
A: Ask yourself, “Which of our strategic initiatives can be achieved with inaccurate, inconsistent and disconnected information?” Most executives know that the business-critical data in their applications, used by employees across the globe, is not the highest quality. But they are shocked to learn how much this is costing the company. My advice is talk to IT about the current state of your customer, product and asset information. Find out if it is holding you back from achieving your strategic initiatives.
Also, many business executives are excited about the prospect of analyzing “Big Data” to gain revenue-generating insights about customers. But the business-critical data about customers, products and assets is often in terrible shape. To use an analogy: look at a wheat field and imagine the bread it will yield. But don’t forget if you don’t separate the grain from the chaff you’ll be disappointed with the outcome. If you are working on a Big Data initiative, don’t forget to invest in the integrated information management infrastructure required to give you the clean, consistent and connected information you need to achieve great things.
Murphy’s First Law of Bad Data – If You Make A Small Change Without Involving Your Client – You Will Waste Heaps Of Money
I have not used my personal encounter with bad data management for over a year but a couple of weeks ago I was compelled to revive it. Why you ask? Well, a complete stranger started to receive one of my friend’s text messages – including mine – and it took days for him to detect it and a week later nobody at this North American wireless operator had been able to fix it. This coincided with a meeting I had with a European telco’s enterprise architecture team. There was no better way to illustrate to them how a customer reacts and the risk to their operations, when communication breaks down due to just one tiny thing changing – say, his address (or in the SMS case, some random SIM mapping – another type of address).
In my case, I moved about 250 miles within the United States a couple of years ago and this seemingly common experience triggered a plethora of communication screw ups across every merchant a residential household engages with frequently, e.g. your bank, your insurer, your wireless carrier, your average retail clothing store, etc.
For more than two full years after my move to a new state, the following things continued to pop up on a monthly basis due to my incorrect customer data:
- In case of my old satellite TV provider they got to me (correct person) but with a misspelled last name at my correct, new address.
- My bank put me in a bit of a pickle as they sent “important tax documentation”, which I did not want to open as my new tenants’ names (in the house I just vacated) was on the letter but with my new home’s address.
- My mortgage lender sends me a refinancing offer to my new address (right person & right address) but with my wife’s as well as my name completely butchered.
- My wife’s airline, where she enjoys the highest level of frequent flyer status, continually mails her offers duplicating her last name as her first name.
- A high-end furniture retailer sends two 100-page glossy catalogs probably costing $80 each to our address – one for me, one for her.
- A national health insurer sends “sensitive health information” (disclosed on envelope) to my new residence’s address but for the prior owner.
- My legacy operator turns on the wrong premium channels on half my set-top boxes.
- The same operator sends me a SMS the next day thanking me for switching to electronic billing as part of my move, which I did not sign up for, followed by payment notices (as I did not get my invoice in the mail). When I called this error out for the next three months by calling their contact center and indicating how much revenue I generate for them across all services, they counter with “sorry, we don’t have access to the wireless account data”, “you will see it change on the next bill cycle” and “you show as paper billing in our system today”.
Ignoring the potential for data privacy law suits, you start wondering how long you have to be a customer and how much money you need to spend with a merchant (and they need to waste) for them to take changes to your data more seriously. And this are not even merchants to whom I am brand new – these guys have known me and taken my money for years!
One thing I nearly forgot…these mailings all happened at least once a month on average, sometimes twice over 2 years. If I do some pigeon math here, I would have estimated the postage and production cost alone to run in the hundreds of dollars.
However, the most egregious trespass though belonged to my home owner’s insurance carrier (HOI), who was also my mortgage broker. They had a double whammy in store for me. First, I received a cancellation notice from the HOI for my old residence indicating they had cancelled my policy as the last payment was not received and that any claims will be denied as a consequence. Then, my new residence’s HOI advised they added my old home’s HOI to my account.
After wondering what I could have possibly done to trigger this, I called all four parties (not three as the mortgage firm did not share data with the insurance broker side – surprise, surprise) to find out what had happened.
It turns out that I had to explain and prove to all of them how one party’s data change during my move erroneously exposed me to liability. It felt like the old days, when seedy telco sales people needed only your name and phone number and associate it with some sort of promotion (back of a raffle card to win a new car), you never took part in, to switch your long distance carrier and present you with a $400 bill the coming month. Yes, that also happened to me…many years ago. Here again, the consumer had to do all the legwork when someone (not an automatic process!) switched some entry without any oversight or review triggering hours of wasted effort on their and my side.
We can argue all day long if these screw ups are due to bad processes or bad data, but in all reality, even processes are triggered from some sort of underlying event, which is something as mundane as a database field’s flag being updated when your last purchase puts you in a new marketing segment.
Now imagine you get married and you wife changes her name. With all these company internal (CRM, Billing, ERP), free public (property tax), commercial (credit bureaus, mailing lists) and social media data sources out there, you would think such everyday changes could get picked up quicker and automatically. If not automatically, then should there not be some sort of trigger to kick off a “governance” process; something along the lines of “email/call the customer if attribute X has changed” or “please log into your account and update your information – we heard you moved”. If American Express was able to detect ten years ago that someone purchased $500 worth of product with your credit card at a gas station or some lingerie website, known for fraudulent activity, why not your bank or insurer, who know even more about you? And yes, that happened to me as well.
Tell me about one of your “data-driven” horror scenarios?
I recently had a lengthy conversation with a business executive of a European telco. His biggest concern was to not only understand the motivations and related characteristics of consumers but to accomplish this insight much faster than before. Given available resources and current priorities this is something unattainable for many operators.
Unlike a few years ago – remember the time before iPad – his organization today is awash with data points from millions of devices, hundreds of device types and many applications.
One way for him to understand consumer motivation; and therefore intentions, is to get a better view of a user’s network and all related interactions and transactions. This includes his family household, friends and business network (also a type of household). The purpose of householding is to capture social and commercial relationships in a grouping of individuals (or businesses or both mixed together) in order to identify patterns (context), which can be exploited to better serve a customer a new individual product or bundle upsell, to push relevant apps, audio and video content.
Let’s add another layer of complexity by understanding not only who a subscriber is, who he knows and how often he interacts with these contacts and the services he has access to via one or more devices but also where he physically is at the moment he interacts. You may also combine this with customer service and (summarized) network performance data to understand who is high-value, high-overhead and/or high in customer experience. Most importantly, you will also be able to assess who will do what next and why.
Some of you may be thinking “Oh gosh, the next NSA program in the making”. Well, it may sound like it but the reality is that this data is out there today, available and interpretable if cleaned up, structured and linked and served in real time. Not only do data quality, ETL, analytical and master data systems provide the data backbone for this reality but process-based systems dealing with the systematic real-time engagement of consumers are the tool to make it actionable. If you add some sort of privacy rules using database or application-level masking technologies, most of us would feel more comfortable about this proposition.
This may feel like a massive project but as many things in IT life; it depends on how you scope it. I am a big fan of incremental mastering of increasingly more attributes of certain customer segments, business units, geographies, where lessons learnt can be replicated over and over to scale. Moreover, I am a big fan of figuring out what you are trying to achieve before even attempting to tackle it.
The beauty behind a “small” data backbone – more about “small data” in a future post – is that if a certain concept does not pan out in terms of effort or result, you have just wasted a small pile of cash instead of the $2 million for a complete throw-away. For example: if you initially decided that the central lynch pin in your household hub & spoke is the person, who owns the most contracts with you rather than the person who pays the bills every month or who has the largest average monthly bill, moving to an alternative perspective does not impact all services, all departments and all clients. Nevertheless, the role of each user in the network must be defined over time to achieve context, i.e. who is a contract signee, who is a payer, who is a user, who is an influencer, who is an employer, etc.
Why is this important to a business? It is because without the knowledge of who consumes, who pays for and who influences the purchase/change of a service/product, how can one create the right offers and target them to the right individual.
However, in order to make this initial call about household definition and scope or look at the options available and sensible, you have to look at social and cultural conventions, what you are trying to accomplish commercially and your current data set’s ability to achieve anything without a massive enrichment program. A couple of years ago, at a Middle Eastern operator, it was very clear that the local patriarchal society dictated that the center of this hub and spoke model was the oldest, non-retired male in the household, as all contracts down to children of cousins would typically run under his name. The goal was to capture extended family relationships more accurately and completely in order to create and sell new family-type bundles for greater market penetration and maximize usage given new bandwidth capacity.
As a parallel track aside from further rollout to other departments, customer segments and geos, you may also want to start thinking like another European operator I engaged a couple of years ago. They were trying to outsource some data validation and enrichment to their subscribers, which allowed for a more accurate and timely capture of changes, often life-style changes (moves, marriages, new job). The operator could then offer new bundles and roaming upsells. As a side effect, it also created a sense of empowerment and engagement in the client base.
I see bits and pieces of some of this being used when I switch on my home communication systems running broadband signal through my X-Box or set-top box into my TV using Netflix and Hulu and gaming. Moreover, a US cable operator actively promotes a “moving” package to help make sure you do not miss a single minute of entertainment when relocating.
Every time now I switch on my TV, I get content suggested to me. If telecommunication services would now be a bit more competitive in the US (an odd thing to say in every respect) and prices would come down to European levels, I would actually take advantage of the offer. And then there is the log-on pop up asking me to subscribe (or throubleshoot) a channel I have already subscribed to. Wonder who or what automated process switched that flag.
Ultimately, there cannot be a good customer experience without understanding customer intentions. I would love to hear stories from other practitioners on what they have seen in such respect