• download
  • Print
  • Recommend
  • 100

How Operations Research Drives Success at P&G

Tags: Team, Procter & Gamble Co., Wegryn, Team Management, Research & Development, Productivity, Branding, Financial Planning, Tools & Techniques, Management, Business Operations, Marketing, Finance, Andrew Hines, Operations Research, Analytics, Quantitative Analysis, Jake Swearingen, BNET Feature


You can’t just call it a company anymore — it’s more of an economy unto itself. With $76 billion in annual sales, 138,000 employees, and operations in more than 80 countries, Procter & Gamble, the world’s biggest consumer goods company, has grown to such epic proportions that economists consider it a bellwether of consumer spending and confidence. Among the more than 300 brands it sells globally, from Gillette and Crest to Scope and Swiffer, 22 generate more than $1 billion in annual revenue. Another 18 pull in at least $500 million.

Yet there’s an entirely different element of P&G’s success that doesn’t show up on the balance sheet, and which figures into almost every key decision driving sales and profits — from choosing the right brand names to slap on new products to precise juggling of global inventories. The secret ingredient? Data — some 900 terabytes of total capacity, 50 TB more than Google searches every day — that P&G uses to measure and optimize almost everything it does.

Three decades ago, P&G’s cadre of data analysts was programming simplistic queries into mainframe computers to determine, for instance, the best time of day to deploy television advertising. It mostly trusted executives’ instincts when deciding when to launch a new product or how much inventory to put on store shelves. These days, thanks to exponentially more powerful computers, data retrieval and storage, and new generations of software, it’s a central army of “quants” at P&G who are arguably as important to its overall success as those storied P&G brand managers.

The company has raced to the forefront of data innovation in recent years, and has turned analytics — or operations research (OR), as it’s more widely known — into a competitive edge that few others fully understand. As Brenda Dietrich, an IBM fellow at IBM’s Watson Research Center, explains, “There’s a gap between the math professionals and the nonmath executives in many companies. The companies who have people who can walk into a business meeting and tell executives how to use OR tools are the ones who’ve got the edge. Deployment is no longer done just by the math people; analytics has become much more usable by a broader set of people within an organization.”

At P&G, it’s top quants like Glenn Wegryn, associate director of product supply analytics, who have quietly led the data revolution. Wegryn’s team of 20 analytics pros combines enterprise-scale simulation and risk assessment software with in-house tool sets to help streamline supply chains, launch new brands, generate internal workflow models and tackle a host of other operational and organizational problems. According to Wegryn, P&G doesn’t make any significant analyses on supply-chain structure without input from his team, since data crunching that can improve the slightest of margins in a company of P&G’s size can generate huge dividends. “The consumer products industry is cost driven, and a lot of it is commodity type in nature,” Wegryn explains. “So very efficient and effective supply chains are critical for success and the ultimate profitability of the company. OR techniques, when utilized effectively, save costs, reduce cash investments and inventory, and can even improve top-line growth.”

P&G, GE, Merrill Lynch, UPS — the list of Fortune 500 companies getting into the OR game is expanding, says Mark Doherty, executive director of the Hanover, MD-based Institute for Operations Research and Management Sciences (INFORMS), an OR think tank. “In the private sector, OR is the secret weapon that helps companies tackle complex problems in manufacturing, supply chain management, health care, and transportation,” he says. “In government, OR helps the military create and evaluate strategies. It also helps the Department of Homeland Security develop models of terrorist threats. That’s why OR is increasingly referred to as the ‘science of better.’”

Rise of the Quants

The current analytics strategy at P&G took root in 1992, when Wegryn and a team of analytic professionals took on a daunting challenge: The company had too many manufacturing plants scattered around the country, and needed to eliminate redundant capacity, figure out optimal inventory holding policies, and develop other techniques that could optimize a supply chain that spanned continents. The data formulas Wegryn began churning through weighed myriad factors, including the impact of NAFTA on operations, trucking deregulation, and redundant capacity issues. The team, which included 30 managers and upwards of 1,000 employees around the country, spent a little less than a year devising tools that generated various consolidation scenarios. The team’s recommendations ultimately allowed P&G to shut down multiple plants and have since generated more than $1 billion in cost savings.

Small wonder, then, why mathematicians are in on business decision making in many companies, not just P&G. Entire companies today — Google, for one — are being built almost entirely on mathematical modeling. “We all know the slogan ‘Intel Inside,’” says Vijay Mehrotra, professor of decision science at San Francisco State University. “But we don’t automatically think, ‘Is there OR inside?’ And yet there is, in a staggering number of things. When you book a car with Hertz, and instead of saying, ‘It’s unavailable,’ they say, ‘It’s available for $59, not $39’ — that’s OR inside. Today it’s embedded in the way we do business.”

P&G’s Killer Apps in OR

Streamlining manufacturing plants was just the start. Here are a handful of other killer apps in OR that Wegryn has since developed and refined at P&G:

New product branding: Several years ago, Wegryn used decision analysis techniques to help managers decide to use Crest as the brand name on Crest White Strips. Granted, that might seem like a no-brainer, but it was a complex decision because the teeth-whitening category was new — a situation in which a new, stand-alone brand name would perhaps make sense. P&G turned to their analytics team to sort matters out, and, as a result, Crest was chosen as the brand. Wegryn says the process involved “getting clear on the question, evaluating options, understanding the uncertainties, and analyzing the best decision that you have available. In the end it was decided to use the brand equity Crest had.”

Sourcing materials: Every product at P&G requires myriad materials, obtained from hundreds of different sources worldwide. Using OR techniques, Wegryn’s team analyzes which source is optimal for every product. “A lot of times, there’s service and quality considerations,” Wegryn says. “We also measure whether a manufacturer really has the capability to deliver the materials at the quoted price.” For instance, retail clients of P&G spend $140 million per year on in-store displays for P&G brands in the United States alone, often buying the display from one vendor. By using OR to determine the best source via a Web interface, P&G now pockets nearly $67 million annually in cost savings and has slashed the order-and-delivery cycle for store displays from 20 weeks to just eight.

International trade and finance: P&G has ground operations in 86 countries, posing huge logistical and financial challenges. With products constantly crossing national borders, P&G is exposed to considerable exchange rate risk, where margins can be squeezed by the tiniest movements in currency. Wegryn’s group taps into software that helps predict optimal exchange rates and allows plant managers to shift production accordingly. “Let’s say there’s one plant in the US and one in Europe,” Wegryn explains. “Based on the exchange rate, we will adjust where we’re manufacturing and sourcing product from. It’s not a massive adjustment, but just a slight adjustment to minimize exchange exposure and maximize the profit, ultimately, for the business.”

Inventory management: At giant-sized P&G, inventory management is crucial to overall efficiency. “How much inventory do I need, and where do I need to have it,” explains Wegryn, “are really simple questions that are really hard to answer.” Using OR, the company now fine-tunes inventory dynamics. For example, conventional wisdom once held that adding a new warehouse to a supply chain would always add inventory into the system as well, ratcheting up costs. But using analytic methods, Wegryn’s team poked holes in this assumption, showing that new inventory need not be added. Their work was able not only to economically justify a new warehouse, but by using better methods, they were also able to track and put exactly the right amount of inventory in the system, reducing overhead costs. “The huge deal about this application of OR is that we’ve been doing it for 15 years,” he says. “It’s used in every area of P&G.”

Organizational design: Wegryn hasn’t aimed OR’s powerful lens on just strategic problems, but internal management challenges as well. Over the past few years, Wegryn has developed simulation models that help execs in each of the company’s five major business organizations keep tabs on their organizational structure and inflow of talent. Taking into account variables such as hiring rates, attrition, retirement, movement between jobs, promotion rates, and so on, the quants created a “flow model” that shows managers what the likely flow of people moving in, out, and within an organization will be over the course of months or years, helping them to determine where they should be hiring most and when.

Toward “OR Inside”

One of the first myths about OR is that it applies only to operational issues. By every measure at P&G, however, OR is a cross-functional discipline applied to anything from executive compensation to inventory management. Wegryn says his analytics group looks at every business problem and asks: “Is it a strategic problem, is it a structural problem, or is it an operational problem? We are called into various problems throughout the entire spectrum.”

P&G’s OR tools fall into four broad categories, according to Wegryn: structured analytical modeling using a spreadsheet-type technology; decision-making analysis methods; mathematical modeling in the form of optimization; and simulation technology.

Within those categories, Wegryn has subsets. One he calls “OR inside” — packaged tool sets from an enterprise vendor. P&G uses outside vendors for optimization software, simulation software, object-based simulation modeling tools, and risk assessment software for decision analysis. Wegryn believes that embedded analytics in commercially available packages are a baseline for any big company to stay in the game. “Our competitors utilize OR tools that are embedded in solutions, as we do, and that is simply to stay competitive.”

But “canned” OR doesn’t come prepackaged with what Wegryn calls “company intelligence” — data that’s specific to the nature of a particular company’s problems and challenges. That’s where “applied OR” comes in. Applied OR is project-specific, utilizing customized tools developed by the company’s analytic team that target particular problems. “We have done analyses throughout the world on very specific questions,” Wegryn says, “like what is the proper balance between capacity at a particular plant and the inventory it should be holding, to help responsiveness to our customers.”

Whatever the application, his team collaborates closely with members of P&G’s IT team — the company’s Global Business Services unit has several hundred employees operating in analytics alone — in order to get the answers to many of P&G’s problems. Says Wegryn: “We develop the algorithms and mathematics inside, but as far as database and systems architecture and deployment and support, we defer to our IT colleagues.”

In the 23 years since she joined Big Blue, IBM’s Dietrich has seen OR evolve “from data gathering that took months and months” to OR available on the desktop. “We can now deliver to executives software that, with a click of a button, can run models and present results. But it takes work to get OR embedded in daily business, and it takes people who can present OR to executives in a concrete way. The bottleneck in OR today is people — the industry is short on people who can deploy OR and frame it in a business context.”

And that is what gives Wegryn his unique status at P&G: He can talk business, and his business counterparts listen. “Rarely are we walking in front of a senior manager without any in-business support for the work we’ve been doing,” he says. “We go off, we analyze options, we come up with a recommended plan, and then we present that to management. Do they throw us out of the office for screwball ideas? The short answer is no. We’ve developed a reputation of having an unbiased view of how the business operates, and we’ve earned their trust.”

Additional reporting by Jake Swearingen.

 
Reply to Story

BNET TalkbackShare your ideas and expertise on this topic

Subscribe to this discussion via Email or RSS

     
  • 1

    josephmartins

    02/14/08 | Report as spam

    OR lovin'

    It's nice to see OR get some love from mainstream media. P&G is certainly not the first to place OR front-and-center in decision making, but I'm glad its use of OR gets the attention of journalists.

    Let OR run the ball to the 5, and let experience take it home.

    This almost makes all those student loan payments worthwhile.

  •  
  • 2

    steven.alker

    02/14/08 | Report as spam

    RE: How OR Drives Success at P

    Fascinating and about time that the OR people came out of the closet.

    I had the pleasure of working for a pioneer of OR who was a member of the Institute of Linear Programming back in 1980. Hugh Walton devised an analogue LP system for optimising corporate models. His first success was with English China Clays where he effectively rescued their ailing operation by optimising the production of various clay pits and other resources to meet the global demand for their finished products. His results were published in the Financial Times as early as 1974.

    The beauty of the analogue approach was that it was interactive and an intelligent operator could examine the implications of optimal and sub-optimal solutions. Often, the sub-optimal solutions were more acceptable for political, strategic or even personal executive reasons ? optimising corporate profit in a private company by getting rid of the Chairman?s Yacht or Rolls Royce was often unacceptable.

    Digital methods at the time, though ultimately much more accurate were incapable of producing results in real time and investigating the interplay between resources and constraints during the optimisation process. Getting sub-optimal interim results took all week!

    I have recently started to revive the practice of optimisation in small business marketing as current mathematical models running on a PC are only now capable of producing the interactivity which Hugh?s analogue monsters would.

    By the way, this was a timely and brilliantly written article which will hopefully awaken the SMEA sector to the possibilities. May I have your permission, to publish it on MarketingProfs ? www.marketingprofs.com as a topic on the forum?

    Steve Alker
    Stevea on www.marketingprofs.com and www.salesvisiononline.com

  •  
  • 3

    n-solis

    02/19/08 | Report as spam

    BNET Reprint Info

    Hey, Steve--

    If you want to link to the article, go right ahead. You'll find all the information you need for full-text reprints on this page: http://www.cnetnetworks.com/editorial/permissions.html.

    Best,
    Nicole Solis
    Managing Editor, BNET

  •  
  • 4

    Francois Grobler

    07/09/08 | Report as spam

    OR in the mining industry

    Any tips on the application of OR in the mining industry? We are still struggling to get clients to bite on quantitative modelling (e.g. Monte Carlo Risk Analysis). How do you convince a client that he needs this and that it's not just a "nice to have"...

  •  
  • 5

    behmkj@...

    02/14/08 | Report as spam

    RE: How OR Drives Success at P

    good article,good working model.

  •  
  • 6

    hema_kadali

    02/14/08 | Report as spam

    RE: How OR Drives Success at P

    A great article on OR analytivs

  •  
  • 7

    phil01dav

    02/14/08 | Report as spam

    RE: How OR Drives Success at P

    Operation research is the concept of the future, though it has been effectively deployed to enhance competitiveness as read from the P&G case, its full capabilities would remain evolving for a long time.

  •  
  • 8

    phil01dav

    02/14/08 | Report as spam

    RE: How OR Drives Success at P

    Policy/Standards and OR
    I would be very interested to understand if OR has been used for IT policy/standards to determine:
    * best fit
    * cost of implementation
    * value add
    Has OR been used in P&G in this aspect at all?
    gneal

  •  
  • 9

    Agoma

    02/15/08 | Report as spam

    RE: How OR Drives Success at P

    P&G has demonstrated a clear understanding of Modern supply Chain principles which aims at optimizing efficiences and reducing cost along their value chain from point of sourcing to delivering their product to the customer rather than focussing on functional boundaries..
    Thats why rather than accepting conventional wisdom that a new warehouse would lead to more Inventory and higher costs they evaluated the Impact along their entire supply chain and discovered that overall inpact would be better placement of Inventory at the right place and time, reduced inventories and lower cost. No doubt the use of sophisticated data processing systems have helped them in their valuation of their supply chains giving the number of products they have and the quantum of activities generated regularly in their business.

  •  
  • 10

    chf@...

    02/15/08 | Report as spam

    OR is smart, but ...

    all this is sure impressive, and there's no way one can model complex and ill-structured decision processes for decision support purposes without the help of operations research ; but however powerful OR tools may have become, it happens that quite often they can't model THE WHOLE of the decision process ; some (at least tiny) part of this process is still handled by the human decision maker ...
    therefore, it may be that some interest should be kept for knowledge-based systems (e.g. expert-systems) which aim at modelling expertise, modelling the way (obvioulsy good) decision-makers process information until they reach their final decision.
    e.g; : when a customs agent scans a container, he looks for specific signs of specific risks, and probably OR could handled that complexity at a given time, but what about updating the model when signs of a risk change, when a new risk emerges ? and wouldn't it be faster / easier / reliable to have the agent "think aloud" using then some kind of verbal protocol analysis ?

  •  
  • 11

    rich@...

    02/19/08 | Report as spam

    Agree with OR is smart, BUT...

    Nice article, but I agree with this comment about the limits of OR: these techniques are indeed very powerful, but are conditioned on some important assumptions - time and/or space problem bounds, high quality real-time data, and most important of all - little if any disruptive (e.g., non-linear) changes. (And as they say in financial prospectuses, past performance is not guarantee of future results.) All of this means that the utility of OR is primarily confined to tactical and operations support.

    However, strategy is the basic source of sustainable competitive advantage (per Michael Porter). So what about decisions about re-architecting supply chains (which Wal-Mart wants to do now that competitors have finally replicated their ground-breaking methods and technology) or other decisions over medium and long-term intervals? High quality data is not available, certainly not in the precise quantitative forms demanded by OR. Disruptive events become increasing likely. And adaptive behaviors by individuals and organizations, nations, etc need to be factored into the mix.
    This domain calls for other kinds of techniques, including scenario planning, system dynamics, Monte Carlo methods, complex adaptive systems, and game theory. And, as per chf, explicit methodologies to support decision-making processes, not just complex models. (see www.decpath.com for a more detailed discussion of these issues)

  •  
  • 12

    Analytics4Me

    02/19/08 | Report as spam

    What is OR?

    It's possible that you may be defining "OR" or "Analytics" a bit too narrowly - it is much more than linear programming methods, which I completely agree have limited scope if you use them in purely textbook (non-industrial strength) problems.

    Our shop utilizes a very robust suite of tools - linear, non-linear, decision analysis, dynamic simulation, monte carlo simulation, fundamental and advanced statistical analyses, etc. We believe strongly that a good analytics practictioner can't have too many quality tools in their toolbelts, because at the end of the day you are helping a decision-maker make the best decision possible in light of quantitative and qualitative contraints and uncertainties. It's the role of a seasoned analytics professional to choose the right tool for the job -- and THAT's what makes this work so facinating!

    -Glenn Wegryn

    PS Thanks to Andy and Jake for a great article on OR/Analytics, and thanks also to the readers for your comments, too.

  •  
  • 13

    jeffrey.s.davis

    02/20/08 | Report as spam

    Re:

    Great follow-up comment, Glenn. One question we didn't have room to address in the article: How does a small or midsize company take advantage of all these slick OR tools? Or is OR by definition a practice that ideally requires big scale?

    Jeff Davis
    Executive editor, BNET

  •  
  • 14

    Analytics4Me

    02/20/08 | Report as spam

    Analytics for Small & Medium businesses

    Thanks Jeff. Good question. Small and medium-size companies can leverage several external sources to get started, such as:
    - analytic consultancies, specializing in end-to-end analysis;
    - larger software vendors who have an on-staff consulting capability (while, of course they are attempting to sell their software, piloting for a reasonable fee lets you try before buying and better understand the capabilities the analytic software can bring);
    - a number of universities with quant departments are always looking for businesses to consult with and give their grad students real-life experience on business problem solving.

    As a business develops a better understanding of analytics capability, it may warrant investing in an on-staff analytics resource -- preferably someone who is already within the company who understands the operations and culture of the company. The resource's time could be split between in-house analysis; developing improved data streams for analysis, and coordinating additional analytical work from any of the above sources.

    - Glenn

  •  
  • 15

    boboye

    02/15/08 | Report as spam

    RE: How OR Drives Success at P

    This piece is thought provoking. I have bookmarked. I also shar it with several of my team mates here at Deloitte Nigeria.

    Mobola

  •  
  • 16

    phardin1@...

    02/15/08 | Report as spam

    RE: How OR Drives Success at P

    Great article. I am going to use as a good example to my Principles of Marketing students.

  •  
  • 17

    jgrmathews

    02/15/08 | Report as spam

    RE: How OR Drives Success at P

    Re hOW or Drives Success. Like the person above, I have been looking for something current to 'spice up' a forthcoming workshop on Organisational monitoring - this is most useful. Giles Mathews

  •  
  • 18

    nolens.volens

    02/26/08 | Report as spam

    OR seems closed-door for new job seekers

    As a Master's student in OR background, I completely agree with this article! I believe in the strength of OR and would love to continue pursue it as my career. Although I've heard the saying "the industry is short on people who can deploy OR and frame it in a business context" several times, I'm starting to find it hard to believe when I begin to look for a job in OR field. Most of the jobs out there labeled "supply chain" need little of the OR techniques described in the article but just a strong sense of common sense. But that's not at all what I'm looking for. I'm looking for a technical job as described in Wegryn's analytics team. The kind of stuff that they are doing sounds really exciting! After reading this article, I feel stimulated knowing that there are actually jobs out there that I like! I guess I've been looking in a wrong direction... Any suggestion?
    Thanks a lot for the great article!

  •  
  • 19

    indizyne

    06/27/08 | Report as spam

    Reply to your question

    I would suggest you open up your search a bnit. Not many recruiters are familiar with this field and capture the job title in different ways. Look into the roles that talk about either analytics, analysis, optimization or similar themes. However, chances are mostly l;arge firms would be lloking for people as the software systems can be pretty pricey

  •  
  • 20

    AppliedOR

    07/08/08 | Report as spam

    RE: OR seems closed-door for new job seekers

    I would agree with the previous reply, and add that a large number of companies likely won't have a department or job title with the formal name of "operations research." More than likely, OR skills will be present in a number of areas such as IT, Finance, or Operations, but these jobs may entail other duties as well.

    When looking for jobs outside of the consulting sector, it's important to remember that these companies aren't in business to explore operations research projects. The people, the projects, and the tools are a significant investment that some companies will make, but most will not without a well defined ROI. Also, most companies may not have good technical career paths for OR professionals, so the continuity of OR skills is difficult for some to maintain. More often than not, companies will depend upon outside consultants for OR expertise, and use their internal people for maintenance and support.

    Based on my experience, there's a strong need for analytic skills, but this may not always involve cutting edge OR methods. To build or be a part of these teams, you must be willing to perform basic analytics, and identify and communicate opportunities for more advanced modeling. Since OR projects aren't always high priority, I wouldn't expect to have a long career of multiple projects with one company.

  •  
  • 21

    Rajiur

    02/27/08 | Report as spam

    RE: How OR Drives Success at P

    As an Academic in Industrial Engineering and Management department in a university I completely agree with the article. Inaddition to that, I belive that OR has the potential to improve the standard of living in devloping countries by helping the efficient utilization of limited resources. So this type of article is very much helpfull to the professionals in devloping countries as well. Thank you for sharing a very good and informative write up. Wish you all the best....

    Rajiur

  •  
  • 22

    AppliedOR

    03/07/08 | Report as spam

    Gaining Acceptance

    This article is good example of an OR department with established credibility.

    One question I?ve struggled with in the corporate world is how to position OR within the company and market the techniques throughout the business. Most OR professionals would like to stay focused on analytical tasks, but you have to make a significant effort to market your skills throughout the organization. That mixed role is difficult for the typical OR personality.

    Most OR projects are not small efforts ? requiring analysts, IT professionals, and business experts. Such projects need approval and support from upper management. Until you?ve established the value of OR, it seems best to focus on smaller efforts that provide some return on investment.

    I think many companies are looking for individuals who can market and build these departments from the ground up, rather than the pure analyst. That?s been my experience in companies without a strong OR history. Any comments?

  •  
  • 23

    joji.aguila@...

    03/18/08 | Report as spam

    RE: How OR Drives Success at P

    I'm a huge believer of OR, currently I'm taking my MBA and struggling to learn or re-learn linear programming- I know, just one of those basics. But I want to really understand it and use it in my decision making thought processes. Wish me luck!

  •  
  • 24

    Eisner

    03/26/08 | Report as spam

    How Cornell Operations Research Graduates Have Helped P

    Procter and Gamble has avidly recruited Cornell Operations Research graduates for many years. To learn more about the relationship, which goes back to a 1923 Cornell Industrial Engineering graduate named Alan Mogesen, see http://www.orie.cornell.edu/orie/news/news/profile.cfm?id=31623

The following tags are supported in BNET comments:
<b></b> <i></i> <u></u> <pre></pre>

Leave a Reply

  1. You are currently a guest | Login?
advertisement
Go
advertisement
  • Click Here
  • Click Here
advertisement