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Gray Rule
July 2016 | VOLUME 17, NUMBER 3
Gray Rule
Managing the CRM Abyss: Winning the Battle for Data Quality
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Managing the CRM Abyss: Winning the Battle for Data QualityBy Kristyn Sornat, Marketing Technology Consultant, Sornat Consulting, Nashville, TN
The premise of all Client Relationship Management (CRM) systems is that attorneys will manage their contacts through their email system and sync them into a central firm database, making a single version of a contact ÒknownÓ by many people at the firm. The CRM can then be leveraged for a variety of marketing activities and typically includes the ability to track campaigns, the success rates of such efforts, assisting with networking across the firm, etc. But every law firm with a CRM system deals with data quality issuesÑinaccurate or incomplete data. Many factors make improving data quality difficult but there is hope! This article shows how one firm tackled these issues.

Every firm with a CRM system deals with the issue of data quality—inaccurate or incomplete data. While there are several CRMs in use in legal, the premise is generally the same: attorneys manage contacts through their email provider and share data by “pushing” it into central database, making a single version of a contact “known” by many people at the firm. A lot of factors make improving data quality difficult, including improper staffing and lack of documentation and training. This article explores a case study of how Pillsbury Winthrop Shaw Pittman took their data quality change request backlog from 12,000 to less than 500 in three months, setting them on the right track to maintaining data standards and to gain back attorney confidence in the database.

Like many other firms, retaining focus on the CRM system became difficult as new areas of marketing technology emerged, new projects and initiatives took priority, and yet staffing levels remained the same. Meeting the demands for bio updates and time-sensitive client alerts or “eblasts” often caused day-to-day CRM work to take a back seat. This was compounded by each staff turnover. The impact on CRM was not evident at first, however as the data change requests backlog crept up in to the thousands, it was clear a change in strategy was needed and the Data Quality Improvement Campaign was born.

Importance of Processing Change Requests

In Pillsbury’s CRM system, all new contacts and updates for existing contacts filter into a central place to be reviewed for accuracy before being added to the shared database. Many of these changes come directly from attorneys and assistants, and when they are not processed in a timely manner it hurts the credibility of the CRM tool. Why would attorneys take time to update their contacts properly if past contact changes were submitted but never updated in the CRM? Also, inaccurate CRM data can cause downstream effects, such as people calling the wrong number for a client or an important contact not receiving a newsletter without the relationship attorney’s awareness.

As complimentary contact management tools have been introduced to the industry, such as email signature scrapers, Enterprise Relationship Management (ERM) systems and email sign-up forms, it is tempting to look to these to solve data quality issues. In truth, they can improve very little without properly trained staff and a manageable process to verify and implement new data into the central CRM system. In this case study, the firm found it essential to implement a process for handling internal change requests on a weekly basis, eliminate the backlog of requests, and only then proceed with other tools to help augment their contact data.

The Campaign

Start with the Basics

The first priority was to create a standards guide for processing change requests. This document defines how contact information should be entered into the system, including not only basics, such as formatting addresses and phone numbers, but also more complex things like how to treat deceased contacts. Having a document all team members can reference at any time is essential for both training and higher productivity.

Training Boot Camp

At the beginning of the campaign only two members of the six-person Marketing technology staff could process change requests, including the manager, because the others were not trained. Data quality training can be a daunting task because of the myriad scenarios possible. Many data quality issues are not black and white, and often requires interpretation and good judgment. The standards guide is just that—a starting place but not an exhaustive one that covers every potential data quality situation an employee might encounter. Unique examples include knowing what to do when you find two contacts with the same name in the database but cannot easily tell if they are duplicates, or what to do if two companies have merged.

Our approach to training was to start small, stress repetition and be hands-on. To begin, we reviewed the new standards guide as a team, and then set up one-on-one training processing real-life change requests for each employee. The training began with one type of request, such as phone number changes, and included:

The employee shadowing the trainer processing requests.

The trainer then shadowing the employee.

The employee completing a set of requests alone, leaving ones they were unclear on to review with the trainer.

Once the employee was comfortable with one type of change request, the training began again on several other types until they were able to process an entire day’s change requests with limited questions. Everyone was encouraged to discuss questionable requests amongst the team and we reviewed complicated examples during our weekly team meeting. This approach is time consuming (it took over a month to get everyone trained), but once complete, it paid dividends by speeding the processing rate and limiting mistakes.

Manage the Black Hole that Is Research

Data quality research, which can include searching company websites, checking social media or double-checking with the attorney who made a request, can be compounded. For example, you may verify a contact’s information on their company website to find that the company has merged. This leads you to not only update the one contact, but also the other 50 employees of that company. To do a thorough job, you then use LinkedIn to research and verify if all employees were part of the transition. A task that should have taken one minute now takes upwards of 30.

This type of scenario is common and makes setting a research standard essential to help staff prioritize requests. Differing from the past “research everything” philosophy at Pillsbury, we now allowed change requests for database contacts with only one related attorney or professional to be automatically updated without research. Also, if a change request added information that was missing from a contact, such as a job title, this was automatically accepted. This strategy allows more time to research and verify the accuracy of information for contacts that several attorneys share.

Divide and Conquer

Another challenge was determining how to evenly assign requests to staff. In the past, the team would focus on requests related to one project, a certain type, or just get done what they could each day. It was essential to establish a feasible schedule without having other work responsibilities suffer, including website content management, email marketing distributions, blogs, proposal and experience management databases, etc.

We split the workload by assigning each Marketing Technology employee a day of the week to process new requests submitted on that day. Requests were to be completed before their day occurred the following week. Exceptions for certain types of work were made. For instance, requests related to firm personnel, alumni, and clients, were assigned to the same employee each week in order to keep special processing standards consistent.

The change request inbox was monitored weekly and totals were added to the team status reports and goals, helping to hold everyone accountable to leadership. As we progressed in the campaign, team members started volunteering to help others when a workday was slow or if one person was inundated with more tickets than usual on their day. By the end of three months, the teams productivity improved by 150 percent, which was the equivalent of resolving 2,500 new requests per month.

Choose Your Battles Wisely

Once the new process was implemented, we could then focus on the backlog of 12,000 requests. Although we knew some might contain incorrect, outdated, or incomplete information (especially if they were aged more than a couple of months), all needed to be reviewed in order to find information that was correct. It was decided to invest in an outside resource to assist the team with a sizable portion of the backlog to expedite the campaign. Hiring temporary staff was considered, but we ultimately used Clients First, a consulting group known for their data quality staff and familiarity with our CRM system.

Although it may seem your firm will never win the battle for data quality, do not allow your system to sink into the abyss by ignoring the warning signs, such as a large change request backlog. Even taking small steps, such as setting standards in writing and training more staff to help, can make a large impact on the quality of data in your system and begin to rebuild confidence in the usefulness of CRM for your attorneys and staff.

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