• June 13, 2023
  • By Brian Bissonette, industry principal for investment banking, DealCloud, by Intapp

Successful CRM Does Not Rely on Employee Participation

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The foundation of customer relationship management (CRM) started with sales, helping companies identify and reach out to prospective customers, track their conversations, and log what their customer-facing professionals discussed, agreed to, or secured agreements for. CRM’s much-needed functionality soon expanded to deliver a global view across the company—reaching beyond sales to customer support and success, compliance, staffing, and operations such as product inventory, finance, and HR. This type of access to firm-wide knowledge helped employees better serve clients and made people better at every job across the company.

The market has exerted pressure on existing, sales-focused CRM software vendors to bend to this new need, but conventional CRM’s functionality for gathering and tracking this expanded knowledge has not kept pace. Too often, and especially in industries with unique go-to-market strategies, creating and maintaining a global view of a relationship requires the participation of several contributing individuals within that organization.

The result is an unwelcome claim on employee time and attention devoted to manual entry of data, along with ongoing maintenance and updates, even if the technology provides the capability to store and analyze data using AI and predictive insights.

This heavy reliance on employee participation, coupled with expanded sets of data that companies want to capture and capitalize on, poses a major challenge for adoption, particularly in knowledge-based industries in which the “product” is the people and their insight. In an investment bank or private equity firm, for example, success depends on managing deep business relationships and leveraging internal and external experts on each potential transaction—a process that traditional CRMs were not built to handle. This leaves advisers to manage complex interactions on tools that were built for one-to-one relationships, with little or no reliance on other sources of data.

Data Proliferates and Changes

Continuing with the investment banking theme, firms—whether they are small boutiques or global bulge bracket banks—typically adopt CRM technology with the goal of streamlining and simplifying the burdensome task of housing and analyzing valuable relationship data. Each new transaction, however, introduces advisers to new people, creating new relationships that need to be managed for the benefit of that deal and the all-important “next deal.” Manually capturing the names and contact information of every person on every call and mapping relationship paths is untenably time-consuming, and conventional CRM applications are generally not built for such an exercise anyway.

Knowledge-based industries like financial and professional services have other requirements as well. Compliance, for example, has ascended to the top of the list. Investment banks need not only to capture and track client engagement data, but to share that data with risk and compliance teams, carefully manage data governance ( who can see what), and communicate efficiently, using approved communications channels and media.

These industries also need the ability to track the skills and experience that each employee brings to the organization, which helps determine how to staff engagements and can even influence the focus area of the entire business. Firms typically input this information as new staff joins; however, most records remain relatively stagnant, missing the skill progression and deal experience of individuals as they grow within the company.

The distractions created by the above challenges are compounded in industries like investment banking and private equity, because professionals in those firms are generally known to be extremely busy, regardless of market conditions. The allocation of bankers’ and investors’ time and energy may have shifted in the past 24 months—more pitching and less executing for bankers; more hunting and less harvesting for private equity investors—but ask anyone in the deal ecosystem about CRM and they will tell you that their work requires careful cultivation of a sprawling set of relationships, and they have enough to worry about without the added burden of manually tracking and recording opportunities, interactions, experience, and all the other data used to make a firm successful.

Enter Thoughtful Automation

On the flip side of entering all data manually, some organizations use CRM software that offers to automatically capture all information without regard for the quality of data or business operations it’s intended for. This approach sounds great in theory, but it is often heavier on form than it is on substance, leaving employees with too much information about low-priority relationships, or too little information that is actually accurate, either of which yields just as much frustration as does the ongoing and entirely manual input of data.

Modern data quality automation and relationship intelligence tools, however, can prove to be the perfect middle ground. The most sophisticated CRM today can deliver more value by bringing auto-capture to a new and higher level of sophistication and accuracy, with the support of new AI capabilities that draw out what is truly salient.

This approach lets firms automatically create and maintain contact profiles using, among other things, contact signature scraping. It can also perform quality assurance checks over that relationship information using custom controls in data quality automation. Activity capture can automatically synchronize email and event specifics alongside associated relationships, including details from each activity like date, time and location, and any attachments included in email conversations or event invitations—saving vital time for the employee involved. Added relationship intelligence technology can use all this information to score relationships, suggest pathways to meaningful introductions, reduce key person risk, and prevent overlapping outreach efforts—ultimately improving relationship discovery and automation. 

Automatically updating core contact data such as companies, names, meetings, and emails––along with third-party corporate contact data integrations––creates value within any organization. But it does not replace insights gleaned from face-to-face meetings that are often the foundation of advisory industries. An intelligent CRM system can see those meetings and nudge users to add details and updates with AI-driven notifications, and can capture them where they happen: out of the office, via sophisticated mobile apps, and in Outlook or Gmail, via next-generation plugins. It allows CRM to become a valued, reliable, and updated system that supports employees across functions, teams, and geographies.

CRM Is Conducted for the Employee, Not by the Employee

When busy senior professionals can’t or won’t keep up with manually logging the explosion of data that’s needed for a truly firmwide view, a ripple effect occurs that ends with dwindling technology usage, and destruction of shareholder value. The business risks of CRM failure are real. Without up-to-date relationship data, client development initiatives may fall by the wayside. A lack of informative employee records leads to poorly built account and deal teams, dissatisfying clients and employees alike. And uncovering conflicts becomes nearly impossible without a global view of client data. On top of the operational challenges is the wasted expense of an enterprise technology and the frustration it causes employees.

If organizations are to realize the full potential of CRM, they also have to acknowledge that it can’t exist as a stand-alone technology. The addition of auto-data capture and relationship intelligence is the future for CRM and will help organizations institutionalize valuable information, ensure data quality, and boost user adoption.

Brian Bissonette is industry principal for investment banking at DealCloud, by Intapp. Previously, Bissonette founded and sold a venture-backed software-as-a-service company that served clients in the investment banking, and private equity industries, and prior to that, he spent 13 years as an investment banker, originating and executing M&A and capital markets transactions in the United States and Europe.

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