Deal Maker Relies on Extensive Database
The Wall Street Journal
MARKETS
By DANA MATTIOLI
Jan. 15, 2014 7:38 p.m. ET
RICHMOND, Va.—All investment banks say they focus on clients, but Harris Williams & Co. takes the practice to a new level.
The merger-and-acquisition specialist finds out all it can about executives at companies willing to buy or sell. Among details it gathers: languages they speak, their favorite cocktail and whether they are more window shoppers than reliable bidders.
Harris Williams, based here, is attempting to usher in data-mining techniques that have worked in other industries to answer a perennial Wall Street question: Will a deal be consummated?
Chris Williams, left, Ned Valentine, standing, and Hiter Harris of Harris Williams. A proprietary database is a key to the firm's business strategy. Jay Paul for The Wall Street Journal
For decades, deal makers have relied on personal relationships and connections to get deals done. But Harris Williams maintains that its focus on "predictive analytics"—collecting and analyzing hundreds of thousands of data points in one main computer system shared by the firm—helps it strike deals and minimize time wasted on talks that go nowhere.
Closing deals is every banker's goal because firms receive the bulk of their fees after a sale.
"We know that this knowledge leads to fewer failed deals," said Harris Williams co-founder and managing director Hiter Harris. The bank focuses on deals valued at around $1.5 billion or below involving smaller and midsize companies.
In November, the bank used its data to help guide the sale of automotive-collision-repair company Caliber Collision Centers to Omers Private Equity.
When compiling the initial list of potential buyers, Harris Williams looked at several variables such as whether a company had ever pursued an acquisition in this industry, said co-founder and managing director Chris Williams. When the time came for submitting bids, more than two-thirds of the group Harris invited submitted final offers, all of which were priced at or above where the bank expected them to be, according to Mr. Williams, who said the analytics helped generate that result.
Retailers and tech companies have long embraced predictive analytics, or collecting and crunching reams of data to anticipate future sales preferences.
The effort requires applying algorithms to the data to predict likely future outcomes. It is standard for companies from travel-booking website Orbitz Worldwide Inc. to Amazon.com Inc.
But the techniques are unlikely to gain wide acceptance among deal makers anytime soon. Asked about predictive analytics, some bankers said they don't want to bother inputting information, even if their bank supplies basic call-log software.
"I don't have time for that," said one veteran banker, who added that he would rather spend time meeting with clients than recording what they say.
Plus, sharing isn't exactly part of the sharp-elbowed culture of investment banking, where bonuses can turn on who receives credit for deals within a bank. Some bankers want to keep details of their client relationships private, even from colleagues.
Harris Williams's database was the brainchild of Mr. Harris and Mr. Williams, Harvard Business School classmates.
Mr. Harris, a math major and a self-described nerd, is a compulsive list maker and taskmaster. Across his desk, legal pads carry to-do lists. His Christmas shopping was done in October.
Not long after they started the company in 1991, both men took copious notes on clients, mostly private-equity firms. Back then, rudimentary tracking software sufficed because there weren't that many private-equity firms.
But in the past 30 years, the number of private-equity firms in North America has ballooned, making what Harris Williams bankers do a lot more complicated. In 1984, there were about 67 private-equity firms world-wide, according to data provider Preqin. Today, that number is 5,330.
So, Harris began meticulously chronicling all of its interactions with executives at private-equity firms and corporations. as well as their strategic goals and track record in deals. Its bankers were instructed to write down notes from every phone call, email, dinner and keep tabs on material from quantitative information, like how often a deal maker or firm dropped out of a sales auction before the final round, to personal details, like what years someone ran a marathon.
The thinking was that keeping close to a few dozen clients was relatively easy, but when that group grew into the thousands, they needed a more methodical approach, according to Mr. Harris.
"At the beginning it was pretty primitive," Mr. Harris said. But the important flagpole the bank planted was cultural, he said, especially as the firm itself grew. The bank employs more than 150 bankers across eight offices internationally.
The database has logic built into it, in the form of algorithms, that automatically generate data points bankers can use to predict behavior of potential buyers and sellers. Database training happens as soon as new hires join the firm, he said. The company established early on that if a banker knew something, it had to go in the database.
No one outside the firm has access to the database, including publicly traded PNC Financial Services Group Inc., which bought Harris Williams in 2005.
The data "can make all the difference in the world when you're picking between three companies who all appear to like the business you're selling," said Jay Jester, managing director on the private-equity team from Audax Group. Mr. Jester said he has tapped Harris Williams to help buy and sell a number of companies.
When Harris Williams was trying to help an oil-field-services company sell itself several years ago, executive managing director Ned Valentine persuaded his client's board to meet with a company that submitted a relatively low first bid. Based on the bank's 15 years of data on how this bidder acted in sales processes, Mr. Valentine predicted that the company had a tendency to raise its final bid significantly from its initial offer. So the board agreed to meet with the company, Mr. Valentine recalls. Ultimately, the potential buyer increased its offer by more than 50% and bought the company, he said.
"There is a real, selfish motive to doing this. We want to win," Mr. Williams said.
Write to Dana Mattioli at dana.mattioli@wsj.com
MARKETS
By DANA MATTIOLI
Jan. 15, 2014 7:38 p.m. ET
RICHMOND, Va.—All investment banks say they focus on clients, but Harris Williams & Co. takes the practice to a new level.
The merger-and-acquisition specialist finds out all it can about executives at companies willing to buy or sell. Among details it gathers: languages they speak, their favorite cocktail and whether they are more window shoppers than reliable bidders.
Harris Williams, based here, is attempting to usher in data-mining techniques that have worked in other industries to answer a perennial Wall Street question: Will a deal be consummated?
Chris Williams, left, Ned Valentine, standing, and Hiter Harris of Harris Williams. A proprietary database is a key to the firm's business strategy. Jay Paul for The Wall Street Journal
For decades, deal makers have relied on personal relationships and connections to get deals done. But Harris Williams maintains that its focus on "predictive analytics"—collecting and analyzing hundreds of thousands of data points in one main computer system shared by the firm—helps it strike deals and minimize time wasted on talks that go nowhere.
Closing deals is every banker's goal because firms receive the bulk of their fees after a sale.
"We know that this knowledge leads to fewer failed deals," said Harris Williams co-founder and managing director Hiter Harris. The bank focuses on deals valued at around $1.5 billion or below involving smaller and midsize companies.
In November, the bank used its data to help guide the sale of automotive-collision-repair company Caliber Collision Centers to Omers Private Equity.
When compiling the initial list of potential buyers, Harris Williams looked at several variables such as whether a company had ever pursued an acquisition in this industry, said co-founder and managing director Chris Williams. When the time came for submitting bids, more than two-thirds of the group Harris invited submitted final offers, all of which were priced at or above where the bank expected them to be, according to Mr. Williams, who said the analytics helped generate that result.
Retailers and tech companies have long embraced predictive analytics, or collecting and crunching reams of data to anticipate future sales preferences.
The effort requires applying algorithms to the data to predict likely future outcomes. It is standard for companies from travel-booking website Orbitz Worldwide Inc. to Amazon.com Inc.
But the techniques are unlikely to gain wide acceptance among deal makers anytime soon. Asked about predictive analytics, some bankers said they don't want to bother inputting information, even if their bank supplies basic call-log software.
"I don't have time for that," said one veteran banker, who added that he would rather spend time meeting with clients than recording what they say.
Plus, sharing isn't exactly part of the sharp-elbowed culture of investment banking, where bonuses can turn on who receives credit for deals within a bank. Some bankers want to keep details of their client relationships private, even from colleagues.
Harris Williams's database was the brainchild of Mr. Harris and Mr. Williams, Harvard Business School classmates.
Mr. Harris, a math major and a self-described nerd, is a compulsive list maker and taskmaster. Across his desk, legal pads carry to-do lists. His Christmas shopping was done in October.
Not long after they started the company in 1991, both men took copious notes on clients, mostly private-equity firms. Back then, rudimentary tracking software sufficed because there weren't that many private-equity firms.
But in the past 30 years, the number of private-equity firms in North America has ballooned, making what Harris Williams bankers do a lot more complicated. In 1984, there were about 67 private-equity firms world-wide, according to data provider Preqin. Today, that number is 5,330.
So, Harris began meticulously chronicling all of its interactions with executives at private-equity firms and corporations. as well as their strategic goals and track record in deals. Its bankers were instructed to write down notes from every phone call, email, dinner and keep tabs on material from quantitative information, like how often a deal maker or firm dropped out of a sales auction before the final round, to personal details, like what years someone ran a marathon.
The thinking was that keeping close to a few dozen clients was relatively easy, but when that group grew into the thousands, they needed a more methodical approach, according to Mr. Harris.
"At the beginning it was pretty primitive," Mr. Harris said. But the important flagpole the bank planted was cultural, he said, especially as the firm itself grew. The bank employs more than 150 bankers across eight offices internationally.
The database has logic built into it, in the form of algorithms, that automatically generate data points bankers can use to predict behavior of potential buyers and sellers. Database training happens as soon as new hires join the firm, he said. The company established early on that if a banker knew something, it had to go in the database.
No one outside the firm has access to the database, including publicly traded PNC Financial Services Group Inc., which bought Harris Williams in 2005.
The data "can make all the difference in the world when you're picking between three companies who all appear to like the business you're selling," said Jay Jester, managing director on the private-equity team from Audax Group. Mr. Jester said he has tapped Harris Williams to help buy and sell a number of companies.
When Harris Williams was trying to help an oil-field-services company sell itself several years ago, executive managing director Ned Valentine persuaded his client's board to meet with a company that submitted a relatively low first bid. Based on the bank's 15 years of data on how this bidder acted in sales processes, Mr. Valentine predicted that the company had a tendency to raise its final bid significantly from its initial offer. So the board agreed to meet with the company, Mr. Valentine recalls. Ultimately, the potential buyer increased its offer by more than 50% and bought the company, he said.
"There is a real, selfish motive to doing this. We want to win," Mr. Williams said.
Write to Dana Mattioli at dana.mattioli@wsj.com
0 Response to "Deal Maker Relies on Extensive Database"
Post a Comment