Category Archives: Customers

Data as a Service will ensure that 2015 will be known as “The Year of the Customer!”

Data as a Service

Customers are at the center

Not so long ago, customers were simply faceless names and transactions understood through disjointed sales data and potentially inaccurate contact information.

Over the past few years, we’ve seen companies across industries make remarkable business transformations to become customer-centric organizations. These companies understand that customers are no longer loyal to brands or products alone. Instead, they’re loyal to companies who provide the optimal, most personalized customer experiences.

By understanding more about their customers, their interests, and their interaction preferences, organizations can ultimately encourage increased sales and usage of their products and services.

As we begin 2015 and predict what the next trends will be, I believe that this year will finally be the year that customer centricity becomes the norm – and effective management of data will play the most critical role to date in getting companies to reach their customer centricity goals.

But it won’t necessarily happen overnight. So how should companies get started with this effort?

“A requirement behind customer centricity is the ability to understand customers at a fairly granular level and to be able to identify the customers or the segments of customers who are valuable from the ones who aren’t,” writes Peter Fader (Co-Director of the Wharton Customer Analytics Initiative at the University of Pennsylvania). “If you can’t sort out your customers — if you can’t look at them and know who is good and who is bad — then you can’t be customer centric. That’s step one.”

More and more companies are working through strategies for what Peter Fader describes as step one. They understand their data, and explore ways to utilize this information to gain valuable insights. For example, consider the advancements that Citrix achieved (read more in this case study). By better understanding their customer data, they saw a 20% improvement in lead conversion.

The organizations that have a better understanding of their customers are leading the way by utilizing technology to ensure data accuracy. If their contact data (address, email, and phone) is correct, then they can effectively reach that customer without fail. If their contact data is poor, connecting with customers becomes impossible and can ultimately impact their ability to compete.

Companies like BCBG understand this and are utilizing data quality services to reach up to 15% more customers (read more in this case study).

As companies continue to understand their customer data, they’ll look to fill in the gaps. Sometimes, these gaps are obvious. If a customer’s contact profile has a hole in it – for example a missing phone number – it becomes clear that the hole must be filled.

Utilizing Data as a Service enrichment and validation capabilities, organizations have the opportunity to clean up missing data without wasting a high value customer interaction to ask for their phone number. Instead, they can spend their time selling to this customer.

In addition to filling the contact profile gaps, Data as a Service subscription data is also a great way to expand the view of the customer and learn more about them. Companies can enrich their customer profiles with demographic information or industry data to round out their customer profiles, further supporting their customer-centricity goals.

In 2015, we will see companies utilizing their customer data to form a deeper connection and ultimately increase sales. The habit of “Speaking at” customers will fall by the wayside of true engagement. If customers are the lifeblood of an organization, then, in 2015, we’ll see more and more companies leveraging Data as a Service to increase customer loyalty — and ultimately fuel business growth.

 

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Imagine A New Sheriff In Town

As we renew or reinvent ourselves for 2015, I wanted to share a case of “imagine if” with you and combine it with the narrative of an American frontier town out West, trying to find a new Sheriff – a Wyatt Earp.  In this case the town is a legacy European communications firm and Wyatt and his brothers are the new managers – the change agents.

management

Is your new management posse driving change?

Here is a positive word upfront.  This operator has had some success in rolling outs broadband internet and IPTV products to residential and business clients to replace its dwindling copper install base.  But they are behind the curve on the wireless penetration side due to the number of smaller, agile MVNOs and two other multi-national operators with a high density of brick-and-mortar stores, excellent brand recognition and support infrastructure.  Having more than a handful of brands certainly did not make this any easier for our CSP.   To make matters even more challenging, price pressure is increasingly squeezing all operators in this market.  The ones able to offset the high-cost Capex for spectrum acquisitions and upgrades with lower-cost Opex for running the network and maximizing subscriber profitability, will set themselves up for success (see one of my earlier posts around the same phenomenon in banking).

Not only did they run every single brand on a separate CRM and billing application (including all the various operational and analytical packages), they also ran nearly every customer-facing-service (CFS) within a brand the same dysfunctional way.  In the end, they had over 60 CRM and the same number of billing applications across all copper, fiber, IPTV, SIM-only, mobile residential and business brands.  Granted, this may be a quite excessive example; but nevertheless, it is relevant for many other legacy operators.

As a consequence, their projections indicate they incur over €600,000 annually in maintaining duplicate customer records (ignoring duplicate base product/offer records for now) due to excessive hardware, software and IT operations.  Moreover, they have to stomach about the same amount for ongoing data quality efforts in IT and the business areas across their broadband and multi-play service segments.

Here are some more consequences they projected:

  • €18.3 million in call center productivity improvement
  • €790,000 improvement in profit due to reduced churn
  • €2.3 million reduction in customer acquisition cost
  • And if you include the fixing of duplicate and conflicting product information, add another €7.3 million in profit via billing error and discount reduction (which is inline with our findings from a prior telco engagement)

Despite major business areas not having contributed to the investigation and improvements being often on the conservative side, they projected a 14:1 return ratio between overall benefit amount and total project cost.

Coming back to the “imagine if” aspect now, one would ask how this behemoth of an organization can be fixed.  Well, it will take years but without management (in this case new managers busting through the door), this organization has the chance to become the next Rocky Mountain mining ghost town.

Busting into the cafeteria with new ideas & looking good while doing it?

Busting into the cafeteria with new ideas & looking good while doing it?

The good news is that this operator is seeing some management changes now.  The new folks have a clear understanding that business-as-usual won’t do going forward and that centralization of customer insight (which includes some data elements) has its distinct advantages.  They will tackle new customer analytics, order management, operational data integration (network) and next-best-action use cases incrementally. They know they are in the data, not just the communication business.  They realize they have to show a rapid succession of quick wins rather than make the organization wait a year or more for first results.  They have fairly humble initial requirements to get going as a result.

You can equate this to the new Sheriff not going after the whole organization of the three, corrupt cattle barons, but just the foreman of one of them for starters.  With little cost involved, the Sheriff acquires some first-hand knowledge plus he sends a message, which will likely persuade others to be more cooperative going forward.

What do you think? Is new management the only way to implement drastic changes around customer experience, profitability or at least understanding?

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Posted in Big Data, Business Impact / Benefits, CIO, CMO, Customer Acquisition & Retention, Customer Services, Customers, Data Governance, Data Integration, Data Quality, Enterprise Data Management, Governance, Risk and Compliance, Master Data Management, Operational Efficiency, Product Information Management, Telecommunications, Vertical | Tagged , , , , , , , , , | Leave a comment

Happy Holidays, Happy HoliData.

Happy Holidays, Happy HoliData

In case you have missed our #HappyHoliData series on Twitter and LinkedIn, I decided to provide a short summary of best practices which are unleashing information potential. Simply scroll and click on the case study which is relevant for you and your business. The series touches on different industries and use cases. But all have one thing in common: All consider information quality as key value to their business to deliver the right services or products to the right customer.

HappyHoliData_01 HappyHoliData_02 HappyHoliData_03 HappyHoliData_04 HappyHoliData_05 HappyHoliData_06 HappyHoliData_07 HappyHoliData_08 HappyHoliData_09 HappyHoliData_10 HappyHoliData_11 HappyHoliData_12 HappyHoliData_13 HappyHoliData_14 HappyHoliData_15 HappyHoliData_16 HappyHoliData_17 HappyHoliData_18 HappyHoliData_19 HappyHoliData_20 HappyHoliData_21 HappyHoliData_22 HappyHoliData_23 HappyHoliData_24

Thanks a lot to all my great teammates, who made this series happen.

Happy Holidays, Happy HoliData.

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Posted in B2B, B2B Data Exchange, Banking & Capital Markets, Big Data, CIO, CMO, Customers, Data Governance, Data Quality, Enterprise Data Management, Financial Services, Governance, Risk and Compliance, Manufacturing, Master Data Management, PaaS, PiM, Product Information Management, Retail, SaaS | Tagged , | Leave a comment

Why Retailers Forfeit the 30% Omni-Channel Premium

Why Retailers Forfeit the 30% Omni-Channel Shopper Premium

The Omni-Channel Shopper Premium

Omni-channel retailing has attracted a lot of attention in recent years – but many retailers still don’t realize its full potential. After countless man-hours and endless expense, they develop a multi-channel strategy across a range of sales and marketing platforms that is – well – pretty good. But is “pretty good” good enough? When sales and marketing platforms include ecommerce, social media, and mobile apps alongside more traditional methods like brick & mortar store, catalogues and kiosks, why do businesses leave their channel to market incomplete?

Maybe the problem lies in the widespread confusion about omni- vs. multi-channel initiatives. An omni-channel system takes a connected approach to multiple channels, seamlessly integrating customer activities into a single conversation, even when the customer decides, for whatever reason, to switch channel. In omni-channel retailing, the customer can select and change channels in any way that suits them – and the retailer can respond instantly to deliver the experience that the customer needs. Each time the customer interacts with the brand, they generate data that the retailer can use to better anticipate and serve the customer during the next conversation.

So, if omni-channel initiatives are so powerful, why are retailers not taking the next step?

Current Concerns

In a multi-channel system, a retailer grows from a single channel to multiple channels with each channel essentially operating as a separate business unit. Each has its own pricing, promotions, inventories, and back office systems. The omni-channel system integrates all of these channels and their accumulated data into one cohesive view of the business and customer. But many retailers wrongly believe that their organizational structure and systems don’t lend themselves to the new environment.

Many feel that a fundamental redesign of the corporate retail organization – from a single P&L regardless of channel, to “rip and replace” of IT systems – would need to occur at the most basic levels. And many organizations are unsure if the extra time, money and risk to reorganize is worth the advantages promised by an omni-channel strategy. In short, many retailers have adopted a wait-and-see stance before they invest.

However, these retailers can take comfort and guidance from the conclusions of the IDC FutureScape: Worldwide Retail 2015 Predictions conference. Based on a survey of top retailers, the conference predicts that “In 2015, CIOs will invest in omni-channel integration technologies as a top priority to support growth in the omni-channel shopper sales premium of 30%.“

The Future is Now

When retailers invest in omni-channel integration, they essentially design an entirely new supply chain of unified capabilities that can simultaneously handle the demands of their “brick and mortar” stores, their ecommerce sites, and any other channel that they have in place. The retailers that have already done so are already seeing the benefits:

  • Corporations that have invested in omni-channel services are already witnessing an average of 30% increase in sales.
  • The IT departments of these corporations are spending far less time performing the redundant or duplicate tasks required by a multi-channel system.
  • Both structured and unstructured data are more successfully and easily integrated across the company than with a multichannel operation.
  • IT departments can retire older technologies that are no longer performing at their previous levels of efficiency.
  • Consumer impacts on individual channels can now be identified almost immediately and the channels adjusted accordingly.

While many businesses may be cautious about taking the next step, the shopping characteristics of today’s consumer are rapidly changing. Customers are moving into an omni-channel world, whether the retailer is ready or not. This means that the business might be forced to play catch-up to their customers, and perhaps sooner than they might like. Omni-channel initiatives simply reflect, improve and realize the value of this customer behavior. Omni-channel initiatives are about making the individual consumer the main focal point of the business model.

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Is Thanksgiving the Most Data-Driven Holiday?

Is Thanksgiving the Most Data-Driven Holiday?

Thanksgiving: The Most Data-Driven Holiday?

Turkey, cranberry sauce, pumpkin pie… and lots and lots of data on the side. Thanksgiving has to be the most data-driven holiday we have. After Black Friday, we will see a slew of reports and headlines describing how the retail industry’s sales performed.

What are retailers all abuzz about right now as we get closer to the Black Friday / Cyber Monday dates?

This year, retailers are using between 31-50% of their online marketing budget on holiday-related efforts alone, according to the National Retail Federation.

The NRF also projects that almost 20% of the retail industry’s annual sales will come from the holiday period.

This sounds like so much pressure, any retail marketer would crack like a chestnut under it. What’s a marketer to do? Here are some tactics and results around peak season holiday marketing.

Segmentation is a great way to see a big lift in sales. If you have the data to understand your customers and identify emerging segments in your market, you can find new business and directly target it with specific messaging. One recent case reported by Target Marketing Magazine showed a 40% year-over-year sales increase from a new segment that was identified and targeted with tailored messaging. Learn more about getting the most from your customer data in this white paper, “Data Quality Management: Beyond the Basics.”

Know your email sender reputation. You spend so much effort getting the right message out via email marketing with the right timing over different days leading up to Black Friday, Cyber Monday, and Green Monday into December. But a poor email sender reputation can lead to those efforts being blocked or sent to the junk folder instead of to your customers. Global retailer BCBG proactively avoided this, using data validation and cleansing techniques to send their sender reputation sky-high (which you can read more about here.) Don’t let a bad sender reputation limit you during the holidays — especially when it can take up to 15 days to fix a major issue like this. Find out more in this short informative video, “Email Sender Reputation: What Does it Mean to Marketers?”

Everyone, positively everyone, is talking about mobile. Practically every article you come across on the subject of retail industry sales around the peak season holiday mentions mobile in some respect – for very good reason. Shoppers take their phones and tablets shopping with them to compare prices, look for deals, and research their purchases beforehand. The NRF reports that 7 out of 10 retailers they surveyed are putting major investments into their mobile-friendly websites. A well-timed SMS message to your customers with a special deal just for them could work wonders. You can take advantage of the huge popularity of SMS mobile messaging in just a few steps. See how in this SMS Quick-Start Guide created for marketers like you.

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How Citrix is Using Great Data to Build Fortune Teller-Like Marketing

Build Fortune Teller-Like MarketingCitrix: You may not realize you know them, but chances are pretty good that you do.  And chances are also good that we marketers can learn something about achieving fortune teller-like marketing from them!

Citrix is the company that brought you GoToMeeting and a whole host of other mobile workspace solutions that provide virtualization, networking and cloud services.  Their goal is to give their 100 million users in 260,000 organizations across the globe “new ways to work better with seamless and secure access to the apps, files and services they need on any device, wherever they go.”

Citrix LogoCitrix is a company that has been imagining and innovating for over 25 years, and over that time, has seen a complete transformation in their market – virtual solutions and cloud services didn’t even exist when they were founded. Now it’s the backbone of their business.  Their corporate video proudly states that the only constant in this world is change, and that they strive to embrace the “yet to be discovered.”

Having worked with them quite a bit over the past few years, we have seen first-hand how Citrix has demonstrated their ability to embrace change.

The Problem:

Back in 2011, it became clear to Citrix that they had a data problem, and that they would have to make some changes to stay ahead in this hyper competitive market.  Sales & Marketing had identified data as their #1 concern – their data was incomplete, inaccurate, and duplicated in their CRM system.  And with so many different applications in the organization, it was quite difficult to know which application or data source had the most accurate and up-to-date information.  They realized they needed a single source of the truth – one system of reference where all of their global data management practices could be centralized and consistent.

The Solution:

The marketing team realized that they needed to take control of the solution to their data concerns, as their success truly depended upon it.  They brought together their IT department and their systems integration partner, Cognizant to determine a course of action.  Together they forged an overall data governance strategy which would empower the marketing team to manage data centrally – to be responsible for their own success.

Citrix Marketing EnvironmentAs a key element of that data governance / management strategy, they determined that they needed a Master Data Management (MDM) solution to serve as their Single Trusted Source of Customer & Prospect Data.  They did a great deal of research into industry best practices and technology solutions, and decided to select Informatica as their MDM partner. As you can see, Citrix’s environment is not unlike most marketing organizations.  The difference is that they are now able to capture and distribute better customer and prospect data to and from these systems to achieve even better results.  They are leveraging internal data sources and systems like CRM (Salesforce) and marketing automation (Marketo).  Their systems live all over the enterprise, both on premises and in the cloud.  And they leverage analytical tools to analyze and dashboard their results.

The Results:

Citrix strategized and implemented their Single Trusted Source of Customer & Prospect solution in a phased approach throughout 2013 and 2014, and we believe that what they’ve been able to accomplish during that short period of time has been nothing short of phenomenal.  Here are the higlights:

Citrix Achieved Tremendous Results

  • Used Informatica MDM to provide clean, consistent and connected channel partner, customer and prospect data and the relationships between them for use in operational applications (SFDC, BI Reporting and Predictive Analytics)
  • Recognized 20% increase in lead-to-opportunity conversion rates
  • Realized 20% increase in marketing team’s operational efficiency
  • Achieved 50% increase in quality of data at the point of entry, and a 50% reduction in the rate of junk and duplicate data for prospects, existing accounts and contact
  • Delivered a better channel partner and customer experience by renewing all of a customers’ user licenses across product lines at one time and making it easy to identify whitespace opportunities to up-sell more user licenses

That is huge!  Can you imagine the impact on your own marketing organization of a 20% increase in lead-to-opportunity conversion?  Can you imagine the impact of spending 20% less time questioning and manually massaging data to get the information you need?  That’s game changing!

Because Citrix now has great data and great resulting insight, they have been able to take the next step and embark on new fortune teller-like marketing strategies.   As Citrix’s Dagmar Garcia discussed during a recent webinar, “We monitor implicit and explicit behavior of transactional leads and accounts, and then we leverage these insights and previous behaviors to offer net new offers and campaigns to our customers and prospects…  And it’s all based on the quality of data we have within our database.”

I encourage you to take a few minutes to listen to Dagmar discuss Citrix’s project on a recent webinar.  In the webinar, she dives deeper into their project, the project scope and timeline, and to what she means by “fortune telling abilities”.  Also, take a look at the customer story section of the Informatica.com website for the PDF case study.  And, if you’re in the mood to learn more, you can download a complimentary copy of the 2014 Gartner Magic Quadrant for MDM of Customer Data Solutions.

Hat’s off to you Citrix, and we look forward to working with you to continue to change the game even more in the coming months and years!

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Reflections of a Former Analyst

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..

 

 

 

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Posted in Big Data, Business Impact / Benefits, Customers, Data Governance, Data Quality, Hadoop, Healthcare, Life Sciences, Profiling, Retail, Utilities & Energy | 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

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

How Can CEOs Protect Customer Data And Their Own Jobs?

Data Security

Data-centric security

Recently, a number of high-profile data breaches have drawn attention to the impact that compromised data can have on a business. When customer data is breached, the consequences can include:

  • 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.

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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.

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Posted in Big Data, Business Impact / Benefits, Customers, Data Governance, Data Privacy | Tagged , , , , , | Leave a comment