Can U B like P&G?

I read a great article in the McKinsey Quarterly today entitled Inside P&G’s Digital Revolution, about how Procter and Gamble is using digital technology and advanced analytics to revolutionize its business.

I encourage you to read the entire article (note: you may have to register), but in case you’re pressed for time, the first paragraph sums things up nicely:

“Robert McDonald is a CEO on a mission: to make Procter & Gamble the most technologically enabled business in the world… [He is] overseeing the large-scale application of digital technology and advanced analytics across every aspect of P&G’s operations and activities—from the way the consumer goods giant creates molecules in its R&D labs to how it maintains relationships with retailers, manufactures products, builds brands, and interacts with customers. The prize: better innovation, higher productivity, lower costs, and the promise of faster growth.”

A few of P&G’s keys to success:

• Enable better decision-making through real time information (or as close to real time as possible)
• Apply advanced modeling & simulation tools to test new product concepts and new manufacturing & supply chain strategies in the virtual world before spending money in the real world.
• Hire people with great analytical skills, then continually train them & develop those skills at all levels of the organization

I’ll add a couple of thoughts of my own.  First, it starts at the top.  P&G’s CEO, Robert McDonald, is not just bought into the strategy, he understands the details and is an active champion for using technology and advanced analytics to drive his business.  

Second, the competition is moving fast so there’s no time to waste.  Get started now.  Don’t wait for perfect data – use what you have today, BUT… do your best to build in data integrity from the beginning so poor data integrity doesn’t come back to bite you later.

Few companies have the resources and capabilities to be like P&G.  But almost any company can use P&G as an aspirational ideal – an example to shoot for as you develop your own analytics strategy.

Ask yourself a few questions about your business:

• How are you using advanced analytics to drive your business? 
• Do you know what parts of your business offer the greatest opportunity?
• What information do you have today that you can leverage for greater insights and improved business results?
• What information that you don’t have today would have the most value?  What’s the next step to getting that data (or at least getting closer to it)?

Until next time…

Rob

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Rob Ende is Founder and President of REanalyze Inc., a Supply Chain, Inventory Management and Analytics consultancy based on Long Island, New York.  Rob can be reached at 631-807-2339 or rende@reanalyzeinc.com.

© 2011 REanalyze.Inc.. All Rights Reserved.

What’s Lurking in your Spreadsheets?

What’s wrong with this formula from a spreadsheet model?

=A2*.18

Seems simple enough.  Imagine you’re calculating an annual inventory holding cost.  Cell A2 contains the inventory value in dollars, and you estimate the annual holding cost percentage at 18%.  Multiply them together and you’ve got the correct answer, right?

Technically, yes.  But…

• What if the holding cost percentage changes next year?  Will you or an analyst or whoever uses this spreadsheet remember to change the formula?

• What if different items have different holding costs?  For example, obsolete items might require a higher value due to the risk of write-offs.

• What if someone passes this spreadsheet along to a colleague working on a different product line, where the holding cost percentage should be 25% instead of 18%?

Any time a parameter like this is fixed or “hard-coded” in a formula, rather than in an input cell, you are much more likely to get burned in one of these situations.  If you are lucky, this is only an informational report.  But what if it’s in a financial model that you use to set operating budgets?  Or to calculate someone’s bonus?

In this case, the solution is pretty simple.  Just put the holding cost percentage into an input cell (or maybe a range of input cells for different products).  Highlight the cell with shading and borders for good measure.  That way anyone who uses the model can easily see the value and change it if necessary.  Even better, give the input cell a name like “HoldingCost” and then you can put it into a formula anywhere in your spreadsheet without having to remember what cell it’s in.

This may seem ridiculously easy, and it is.  But you would be amazed at how prevalent poor practices like these are in otherwise very sophisticated companies.  Virtually every business uses Excel spreadsheets to a lesser or greater extent.  And no matter where I’ve been in my career as an analyst, an executive and a consultant – small and large companies, different functional areas, various industries – I have seen poor modeling practices and outright mistakes in almost every spreadsheet I’ve come across.   In fact, some people have remarked that I have a special talent for finding this stuff!  Some are obvious formula errors.  Others, a result that “just doesn’t look right” based on what I know about the business (note:  the published research on spreadsheet errors is a little scary: See this literature review from Powell, Baker & Lawson or this research article from Panko).

When you get right down to it, spreadsheets are software that perform some function or process for your business.  But unlike other types of software, which are usually developed by trained software developers with a controlled process, just about anyone can create or modify a spreadsheet.  Think about all the rigor and quality control that go into typical software development in your company.  Then think about whether your spreadsheets are getting a comparable level of attention.  If not, you could be introducing a lot of uncertainty and risk into your business.

In upcoming posts I’ll point out some other problems to look for in your spreadsheet models, along with some best practices to reduce the risk to your business.  You may consider starting with a "No fixed values" or "No hard-coded constants" rule for your spreadsheet developers.

In the meantime, here’s something to think about.   

Do you run critical parts of your business on spreadsheets?  If so, have you thought about where and how they are being developed, and what sorts of errors may be lurking inside?

Until next time…

Rob

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Rob Ende is Founder and President of REanalyze Inc., a Supply Chain, Inventory Management and Analytics consultancy based on Long Island, New York.  Rob can be reached at 631-807-2339 or rende@reanalyzeinc.com.

© 2011 REanalyze.Inc.. All Rights Reserved.

In Supply Chain Planning, One Size Does Not Fit All

Supply Chain leaders recognize that their planning processes need to be tailored to the attributes or characteristics of specific items.  However, many manufacturing and distribution companies still use"one-size-fits-all" approaches to Demand and Supply Planning.  This often results in too much inventory on some items, and not enough inventory on others which can cause shortages and stock-outs.

A number of years ago, at Arrow Electronics, we implemented a Categorization approach that applied different forecasting and inventory policies to each item based on the item's demand characteristics, e.g., sales volume, variability of demand and risk profile (mainly, how much of the demand was concentrated with one or a few customers).  This allowed planners to focus on the right items to ensure we had the right amount of inventory in the right place at the right time.  It was a key element of an inventory strategy that improved inventory turns from 3.5 to 6 while improving customer service levels.

Ask yourself these questions:

• Do you use the same forecasting process for all items?  Or do you vary the process based on an item's demand characteristics such as volume, variability or risk?  How about life-cycle stage, i.e., do you forecast new items differently from mature or end-of-life items?

• Do you set your inventory targets or reorder points based on consistent rules-of-thumb, e.g., 30 days coverage ?  Or do you set them based on each item's demand variability, lead time and variability of lead time?

• Do you set lot sizes or MOQ's for production or purchasing based on "gut feel"?  Or do you employ some sort of Economic Order Quantity or Total Cost of Ownership approach to minimize total supply chain costs?

For a good example of what I'm talking about, check out this video from SupplyChainBrain, featuring Tim Conrad of Gates Corporation.  Gates implemented a process called "Plan for Every Part" or PFEP, which tailors Supply Chain and inventory strategies based on each item's unique DNA.   Click here to watch the video.

How well does your company align its Supply Chain Planning processes with the unique characteristics of each item?  Have you thought about the inventory, service and cost benefits of a more tailored approach?

Until next time…

Rob

_________________________________________________________________

Rob Ende is Founder and President of REanalyze Inc., a Supply Chain, Inventory Management and Analytics consultancy based on Long Island, New York.  Rob can be reached at 631-807-2339 or rende@reanalyzeinc.com.

© 2011 REanalyze.Inc.. All Rights Reserved.