By Lisa Yorgey Lester
How Morgan Stanley is shifting from a product-centric to a client-centric organization.
Its directive was clear: to become a premier client-centric organization. Following the publication of its 2000 annual report, in which Chairman and CEO Philip J. Purcell issued this proclamation, Morgan Stanley embarked on a journey that would transform the way the financial services firm does business.
Today, customers have choices. In the financial services industry, in particular, products and services are quickly copied, undifferentiated and unable to maintain a significant and sustainable competitive advantage. Survival hinges on an organization's ability to compete based either on price or superior customer intelligence.
Morgan Stanley chose the latter.
The Reality of Being Customer-centric
Morgan Stanley serves 2.7 million households through its 500 branches. Prospecting in the past largely had been done at the financial advisor level through referrals, cold calls and mailings to rented lists. The goal of becoming a client-centric organization was to make customer acquisition and retention a more analytical and measurable process that would be consistent across all financial advisors.
Recognizing that no organization can be all things to all clients, Morgan Stanley wanted to arm its financial advisors with information they could use to pursue the types of clients the organization wants, and not waste time chasing clients it doesn't want and who would be better served elsewhere. To grow its business, Morgan Stanley needed to acquire more targeted clients that fit with its offerings; increase its share of wallet with its existing customers; and retain its most valuable and profitable customers.
To be a world-class marketing organization you need to build a world-class information infrastructure. As part of this initiative, Morgan Stanley hired in May 2001, Tony LoFrumento, a CRM expert who'd spent the last 15 years in retail banking. As executive director of CRM, LoFrumento's assignment was to implement a CRM infrastructure and environment to support the Individual Investor Group and Morgan Stanley Investment Management Divisions.
LoFrumento set about assembling a CRM team with the necessary skills, which includes Chief Statistician Dr. Tom Tao and Business Intelligence Analyst Laura Bartels. To accomplish its objective of implementing and supporting a CRM infrastructure, the CRM team works closely with teams from market research and client technology services to provide the necessary analytics that allow Morgan Stanley to become a client-centric organization.
A Holistic Customer View
The CEO's directive essentially guaranteed that those responsible for implementing a CRM program at Morgan Stanley had the senior management support critical to the success of any CRM initiative. The CRM team's next challenge was to create a holistic view of Morgan Stanley's customers. This required the financial services company to literally change the way it did business.
Traditionally, customer information within financial services organizations is scattered among product silos. No collective view of the customer exists.
LoFrumento firmly believes in the crawl, walk, run method of building a CRM infrastructure and environment. In this case, it meant gathering the data, filling in the gaps, mining and analyzing the data, deriving customer knowledge from it and then getting it into the hands of those who could use it.
So the CRM team began by gathering and assessing all available information. LoFrumento's philosophy: "You must first gather data, transform data into customer knowledge, and make this customer knowledge available throughout the organization."
The CRM Team Vision
A successful CRM initiative starts with the end goal in mind: to understand clients and prospects from all perspectives.
Morgan Stanley's vision: to have such a robust set of information about clients and prospects that it can predict the next product a client is likely to buy. "That's what we're working toward," affirms Justine Metz, executive director, strategic market research and Web site marketing. "We haven't gotten there yet, but that's the coup: getting the data set in place to then be able to analyze different trends within the data, different types of behaviors and build predictive models."
To this end, the CRM team works with Metz and Darryl Dougan, vice president of strategic market research, to make sure client and prospect databases are built such that the firm has information at the client and household levels. This information enables it to understand things such as investor styles or preferences of investing, profitability, basic demographics and product portfolio mix.
"Ultimately, what you want to get to is some sort of equation around lifetime value of the customer, so you can understand where you should be spending your time and energy and putting the best services toward the best clients," Metz contends.
What's more, it can then overlay external data to "determine untapped potential of our existing clients," adds Dougan.
Data Mart Construction
The CRM team now had to begin to implement this vision. The next order of business was to develop an infrastructure to initially deliver customer-centric information where it would have the largest organizational impact—primarily its sales force, who are financial advisors. At the time, a national operations data mart was being built as part of a larger data warehouse infrastructure set to be turned over for production on September 11, 2001. As a resident of tower two of the World Trade Center, "We lost all our hardware and software; luckily having our data backed up, we were able to rebuild our infrastructure using this saved data and the team's knowledge of the CRM infrastructure," recalls Vice President Michael Strachan. Working offsite, Strachan and three key team members were able to coordinate and rebuild this infrastructure within two months with the help of a LAN (local area network) and other IT support staff.
The system was reincarnated as a CRM data mart. Information on customer transactions at the product-holding level-—equities, fixed income, mutual funds, managed futures, insurance—were pulled from various legacy systems and loaded into the CRM data mart. These account-level data were then transformed into customer-level data using a householding algorithm. Now, Morgan Stanley could view a client's total managed assets at the individual or household level, rather than by account.
This information also feeds SAS's Marketing Automation Solution for data mining, predictive modeling, performance measurement and campaign management, including audience selection criteria for various campaigns and back-end analysis.
At this point, says Metz, the CRM data mart could provide basic transaction data on current clients—what products clients owned, account numbers and a little bit of demographic data. This information was supplemented with off-the-shelf demographic data, as well as with information from other systems within the company, such as assets under management. What was missing, however, was the investor attitudinal component—the firm didn't understand its investor profiles and preferences.
So Metz and Dougan commissioned a piece of proprietary research, and from that they identified six distinct types of investors, explains Metz. Using this information, Dougan built a predictive model to help financial advisors easily determine a client's style of investing.
Financial services companies traditionally segment their clients on very basic, commonly acquired dimensions such as assets and age, according to Metz. An example might be selecting high net worth investors and then further segmenting by age—for example, high net worth investors who are married and over the age of 50. Based on these dimensions all investors within this segment look the same, explains Metz. However, she points out that "not everyone who's 55 and has a million dollars in assets under management has the same types of investing preferences and styles."
By overlaying investor-style data, Metz and Dougan identified and prioritized six different types of Morgan Stanley investors. This knowledge has allowed the firm to focus its communications and service delivery to certain types of investors.
The firm's 2002 IRA Rollover campaign is one example. Rather than mail its entire base, as it had in the past, a predictive model was used to select the appropriate audience of investors from its CRM data mart. This list of households was then sent to the financial advisors for follow-up by mail or phone.
To measure the campaign's success, the CRM team matched new accounts against the list of households, and saw a 40-percent lift in the number of accounts opened during the same period the previous year.
Data in Action
This knowledge also has to be transferred and put into the hands of the people who are on the frontlines and who interact with customers—the financial advisors and sales support personnel.
To achieve this goal, the CRM Group developed the Business Intelligence System (BIS). Powered by Business Objects' Web Intelligence Solution and delivered through the company's intranet, BIS delivers a series of reports that provide a holistic view of Morgan Stanley clients with critical information that enables the sales force to better understand and thus better meet the needs of the clients.
Says Dougan: "Our ability to segment our clients and use that information as well as internal data has been applied to existing client bases so that financial advisors can understand who they should be spending more of their time with." He explains that some clients expect frequent contact and a good deal of interaction with their financial advisors, while other clients prefer to delegate responsibility and don't need as much interaction or frequency of contact.
To make this a reality, Dougan built a predictive model financial advisors could use to determine into which segment a new client falls—without having to become a statistician. Strachan says he knew the most efficient way to get this information out to its sales force in a user-friendly manner was via the Web. And so after evaluating various tools, Morgan Stanley developed a Web-based application to address this need.
This application allows financial advisors to enter clients' responses to a set of survey questions directly from their workstations. The application then delivers to financial advisors—in real time—the segment of a client to allow for a customized sales approach on the spot. It also sends the results to the CRM data mart so this critical attitudinal information can be used in future efforts to better understand and meet the needs of the clients.
To further help its advisors get the maximum benefit from this Web-based tool, the team created and made available a variety of communication vehicles for each of its six investor types, including talking points, prospect letters, client letters as well as two-page summaries of detailed research.
Buying Into the CRM Process
No matter how much money is invested or how many hours it takes to build, a CRM tool is only good if it is used.
Once an initiative is in the works, such as the segmentation project, a multimedia campaign using Morgan Stanley's central TV network system, e-mail, field kits and other materials is built to create awareness among the financial advisors.
Says Dougan: "When creating these internal campaigns for the financial advisors to create awareness, there has to be a value proposition for the financial advisor," says Dougan. "It has to be: How can we improve their productivity, how can we improve their success rate, and how can we allow them to be more productive servicing and dealing with more clients with less effort? And that comes from understanding what exactly the client wants."
He continues: "I think we've been able with our particular tool to answer those questions, and the demand has come. It only takes a few uses of it for them to see how it can help them in their day-to-day business."
LoFrumento wholeheartedly believes business decisions need to be made based on facts, not conventional wisdom. Customer profitability, he stresses, must be measured, otherwise you risk investing valuable resources on unprofitable customers, while profitable customers remain underserved.
Retention is measured by segment. LoFrumento explains: "In a client-focused organization, you want to have your highest retention rates for your most valuable and profitable segments."
Too often, he says, "companies don't realize who their best customers truly are, but their analytically savvy competitors do, and these customers are quietly siphoned off by these competitors."
By knowing who your top clients are, LoFrumento says, you can "match the appropriate level of service and offerings commensurate with their value."