New York, NY April 16, 2012— Now in its sixth decade, the Ellis R. Ott Workshop in 2012 offers attendees the opportunity to obtain an immediate return on time invested using practical quality tools and methodologies in a personalized instructor-facilitated setting. The one-day conference will take place on Thursday June 21, 2012.

This year’s theme, “Learn it Today, Use it Monday,” consists of workshop-based programs focusing on immediate skills development. Each of the three tracks, ranging from business process models to simple six sigma solutions using Excel to “a quality system in two pages” consists of hands-on sessions whose tangible results can be immediately applied upon returning to the office.

This year’s workshops feature Thomas Pyzdek, renowned business advisor and founder of the Pyzdek Institute, Jay Arthur, six sigma thought leader and president of Know Ware International and Michael Mickelwright, lean quality systems advocate and columnist for Quality Digest.

To enhance the quality of the face to face instruction, class sizes will limited.

ABOUT THE ELLIS R. OTT CONFERENCE

The Ellis R. Ott Workshops were founded in the 1940s by Dr. Ellis R. Ott, a Rutgers professor and early proponent of statistical quality control methodologies in American industry. Originally started as the All Day Quality Conference on Quality Control and Statistics in Industry at Rutgers University, the NY/NJ Metropolitan Section of the American Society for Quality is proud to continue the tradition of fostering practical business skills in the ever evolving contemporary quality profession. The conference honors the legacy of Dr. Ott, who was a founding member of the NY/NJ Metropolitan Section and himself served as Section Chair in 1950.

ABOUT THE ASQ NEW YORK/ NEW JERSEY METROPOLITAN SECTION

The NY/NJ Metropolitan Section, founded in 1946 by leaders of the modern quality profession such as William Edwards Deming, Joseph Juran, Ellis R. Ott, Harold Dodge and Walter Shewhart, is the premier forum for quality professionals in Greater New York City area. Located in one of the most vibrant and diverse regions in the world, the Metropolitan section is a multi-disciplinary, cross-functional section, fostering a knowledge-based approach to growing the profession’s future while building upon the legacy of its foundational past.

For further information and registration, please go to the Metropolitan Section website.

The Toyota Production System (TPS) really is The Machine that Changed the World (see the book of the same title by Womack, Jones and Roos that has sold over 600,000 copies). TPS has changed how every single product is manufactured in every part of the world. One key pillar of the TPS system is Just-in-Time.

Just-in-Time is a production strategy that seeks to improve a business’ Return on Invested Capital by reducing the carrying costs associated with work-in-process (WIP) inventory. It is a pretty simple idea: There is a lot of capital tied up in WIP inventory. If we can reduce it, our costs will go down and ROIC will improve. If we have less inventory, when market demand changes, there aren’t as many write-offs. If we don’t have as much WIP, we don’t need as much space. As big as all of these savings are, they are the tip of the iceberg in terms of the gains wrought by JIT.

What is interesting is that the commitment to that simple JIT idea resulted in a virtuous cycle of changes that produced financial benefits way beyond the reductions in working capital. For example, when you take away the safety stock, all the production abnormalities such as machine reliability, excessive changeover times, and production bottlenecks, start to rear their ugly heads. So implementing JIT unveils production issues that management may not have even been aware of and forces them to improve those inefficiencies to avoid production outages.

Similarly, with only enough parts on hand for the production scheduled for that day, assemblers no longer had a choice of which part to use. Every part available had to work perfectly. If it didn’t, the line would shut down. Just as the commitment to JIT unveiled production problems, it also created a quality assurance crisis. The result was a continuous improvement in the quality of parts that extended back through the entire supply chain.

Further, the improvements in the quality of parts were not always enough. Many companies were also forced to redesign the product to widen tolerances. This had the effect of further improving the quality of finished goods.

The biggest effects of JIT may have been the impact on the customer. The factories were increasingly able to predictably deliver goods on the promise date. They were also more responsive. You no longer had to, in the case of cars, “take what’s on the lot.” You could choose from a blizzard of options and get the exact car you wanted with remarkably little wait time. The quality improved, the choices improved, the responsiveness improved, and guess what? So did customer satisfaction, loyalty, and revenue.

The commitment to this simple idea of Just-in-Time drove dramatic improvements through an organization. Could a commitment to getting every call that comes into a call center correct have a similar, virtuous cycle of effects? I think it can.

Let’s conduct a simple thought experiment augmented by real results. What would happen if we defined what a correct call was, by call type, and our combination of people and technology guaranteed that almost every call would be exactly right?

For this thought experiment, we are going to start with a typical, say financial services, call center. Customers call for lots of reasons…lost credit card, transaction inquiry, credit limit increases, etc. We have some calls well documented, some not so much. We have some good agents, others not so good. Agents make mistakes sometimes: they skip steps or don’t follow the most updated procedure. Some are crisp, others take a lot of time and there are a couple minutes of after call work, where the agent has to clean up the call and, ahem, take a little break.

Then we will assume that we make some changes. We define what a correct call is for every single call type…what the agent must do in their system and say to customers to correctly resolve their issues. And we will assume we have figured out a relatively efficient way to handle that request that minimizes handle time and after call work.

To ensure the agents follow the correct process, efficiently, we will deploy agent-assisted automation. Agent-assisted automation involves the use of pre-programmed system actions and pre-recorded audio files that are directed by the agent. The agent is live on the call, following the pre-defined path as appropriate, but intervening with his/her live voice whenever what is happening on the call requires it.

What follows is a list of benefits that would accrue if we got the calls right. As you go through the list, actual results we have achieved using our automation and the degree of benefit we have seen are shown parenthetically.

1) If we are using some automation, there is less to teach the agents. If there is less to teach the agents we could reduce the lead time we need for hiring agents in advance of when they need to be on the phones. (Our client reduced training time by 30%.)

2) If the automation is ensuring the calls are correct, we do not have to pull the agents off the phone for training/coaching as often which means we don’t need as many agents to hit service levels. (Call volume is up due to the growth of the product, but the number of agents has been reduced.)

3) If we know the calls will be right, we don’t need to do as much monitoring, which means we need less monitors.

4) If the call is right, we will get less repeat calls, which means we will have less volume and need less agents. (same as #2)

5) Because we have engineered the calls, they are shorter and there is less After Call Work. This reduces the number of agents we need. (We have reduced AHT by 40% and ACW by 90%.)

6) If the automation is handling the boring and fatiguing parts of the job, the agents may be happier which will delay turnover. No one stays in the job forever, but delaying turnover is the same as reducing it. (We have dramatically improved agent satisfaction, but we do not have long term data on the effect on turnover.)

7) If we have less agents and less turnover, it means we

a. don’t need as much HR staff to hire, fire, and administer

b. don’t need as many managers/coaches

c. don’t need as many seat licenses for software and hardware

d. don’t need as much space

8) When agents make mistakes costs often occur outside the call center. There can be big groups handling improper warranty returns, calls get escalated to supervisors, letters get written to the CEO, legal gets involved to handle mistakes made by agents, fines have to be paid, etc. If the calls are handled correctly, all of this work goes down and may result in the need for less staff. (We have reduced legal fees and accent escalations.)

9) Often times the steps agents skip or don’t do correctly are cross-sells. If these are done every time, revenue goes up because the agent makes the right offer at the right time, every time. (We have increased cross-sell by 5X over agents not using the automation.)

10) Usually when calls are streamlined, it means less AHT, which is important. But when the calls you are streamlining are collections calls, handling more calls per day means collecting more revenue. (Record revenues have been achieved by agencies using our solution…up 25% over target)

In manufacturing, all the WIP lying around was pure waste that covered a lot of other problems. Similarly, there is a lot of waste in and around call centers that is a direct result of the inefficiency and ineffectiveness of call center agents.

I am not blaming the agents. Call handling work is poorly designed, the job is fatiguing, the pay is low, turnover is high, and humans make mistakes. The thought that sporadic coaching could overcome all of these problems and provide a way out of the wilderness is laughable. But combining the accuracy and reliability of software automation with the warmth and flexibility of human interaction has been shown to dramatically increase the percentage of correct calls.

I am guessing when companies started with JIT, no one imagined that a simple commitment to reduce the waste associated with excess inventory would have the far reaching effects that it had.

Could a simple focus on getting calls right hold the same potential?

Every industrial facility that uses indoor vehicles such as forklifts are required by OSHA to mark the aisles and passageways for the safety of pedestrians. The method that is used for maintaining a highly visible floor marking may be creating unnecessary waste. Considering that this aisle marking will need to remain in place for the lifetime of the facility, let’s take a look at how the method used for creating and maintaining that marking could be causing wasted materials and wasted manpower. After all, OSHA’s floor marking requirement is not likely to change.

Aisles and passageways are commonly marked with paint, so let’s look at what is involved in using paint to mark the floor over the long term life of the facility. Paint does not adhere well to concrete, so the floor must usually be prepped by bead blasting or etching to rough up the surface so that the paint will have something to grab.

To create a nice clean line to delineate the walkway, two stripes of tape are applied to create a template for the paint. Multiple coats of paint are applied, allowing dry time after each coat. Often production lines must be shut down to allow the paint to dry completely. The entire process could take a few days, and so the cost of the loss of production should be factored in to the overall cost of using paint to mark the line. Then the tape borders must be removed as well.

When the area is open again to traffic, the line is subjected to the abuse of the indoor vehicles. Paint does not tend to hold up very well to this constant traffic. I’ve seen painted lines get blackened within a day.  The line will constantly need to be repainted to maintain a higly visible walkway. Basically the entire process has to be repeated.

If there was an alternative method of creating a line that would eliminate the bead blasting floor prep, the shut down time, the tape removal, all while creating a line that lasted longer and required less frequent maintenance, then we could easily say that using paint for floor marking is wasteful.

Fortunately there is an alternative, and that is using a heavy duty floor marking tape to stripe the floors and create the walkways. There is no prep work other than alcohol mopping the floor, and no shut down required. The floor can be opened to traffic immediately after application. If you make sure to get the highest quality floor tape, then the stripe will last for a long time. The highest grade of floor tape features beveled edges and a recessed adhesive system. The beveled edges create a “ramp” effect, allowing traffic to be directed up and over the line. Because the adhesive is recessed away from the edge, the traffic never touches the adhesive, and the tape remains in tact for longer periods of time.

Heavy duty floor marking tape is completely different than standard vinyl floor marking tapes. Be ware of thin vinyl floor tapes, because they are not very durable, and when they need to be replaced, they are very difficult to remove. They do not have a recessed adhesive, and they are prone to tearing. Because they cannot hold up to traffic and are difficult to remove and replace, these tapes are another example of floor marking muda.

Lean initiatives strive to identify muda in every possible manifestation. Waste can be found in almost any process. When it comes to floor marking, consider the waste that can be incurred not only in the initial installation, but in the long term maintenance of the floor marking. To make your operational efficiency as high as possible, take some time to analyze the method of marking aisles and passageways. There may be significant gains in efficiency to be realized.

About the Author:

Cliff Lowe holds two patents in traffic marking materials, and is the owner of InSite Solutions, LLC. He is the creator of Superior Mark floor tape, which has a patent pending design. Free samples of his traffic marking solutions are available online at http://stop-painting.com.

George’s Super-PAC knows how to play political hardball. The one GOP candidate who declined George’s repeated invitations to sign “the Lean Six Sigma Pledge,” Mitt Romney, became the prime target of Strong America Now’s attack ads. “War it was to be,” said George. And war it was. For example, Strong America Now spent $40,552 in an Iowa campaign mailer in late December which branded Romney as “the second-most dangerous man in America.” (After Barack Obama.) George makes it clear that the Super-PAC is a strong-arm tactic to get Romney to sign the pledge. “I’d kill the super-PAC tomorrow,” if he signed, says George.

Perhaps Business Week is a bit unfair with it’s bottom line summary: Newt Gingrich regularly touts Lean Six Sigma, a management strategy created by a rich donor who started a super-PAC to support him. After all, Newt professed to be a fan before the Super-PAC was formed. And Newt took a Lean Six Sigma Class in the 1990s as a Congressman. Still, the level of interest being shown by Newt in Lean Six Sigma is probably not entirely because of its promise to streamline government.

• Click here to view the press release.
• Click here to view the details of the refresher training.

The price of the training is $495 for six months of access, or $82.50 per month.

First, the big picture.  In contact centers no one talks about Six Sigma or Five-9s, or Taguchi’s “on target with minimum variation.” Those ideas are constantly being discussed in manufacturing, but are laughable notions in call centers. No one talks about it.  No one aspires to it.  No one even thinks anything remotely close is even possible.  Further, no one does any benchmarking to see what “world class” companies do so that “stretch goals” can be established around even a “tolerable” level of agent errors.

OK, fine you say, so contact centers don’t set their sites very high.  What if we just went from center to center and determined the error rate and called the average across those centers “acceptable?” You wouldn’t even be able to do that.  In manufacturing, specs are sine qua non and performance against those specs is constantly measured. But for some reason, contact centers rarely even define, by call type, specs or Required Call Components…exactly what the agent is supposed to do in their systems and exactly what information needs to be provided to the customer, let alone measure performance against them.

Consider a quotidian price change for a service where we decide to check the agents’ accuracy in giving the new price. Hate to break it to you, but on the day after the price was changed, there is no way the agents will quote the right price 100% of the time. So then what would be the acceptable error rate? 75%? 80%? Would 45% be OK? What would be acceptable two months after the price change?

We know of one consumer electronics company that listened to 10 out of 10 of their outsourcer’s agents give the old price for a service. The outsourcer didn’t even know their agents were making so many mistakes. The client, of course, was none-to-happy, but the outsourcer didn’t get fired. De facto, the outsourcer’s performance was acceptable. (For more on the sloppy process changes in call centers, see Inside Jokes)

I know what you are thinking. A price change? Come on! What’s the big deal? If the agents get this wrong it is unfortunate, but not the end of the world. OK, then, what would be an acceptable error rate on debt collection calls which are regulated by the Fair Debt Collections Practices Act?

According to the FDCPA, debt collectors are required to disclose to the debtor 1) they are calling from a debt collections agency and 2) their mini-Miranda rights (“…anything you say can be used to help collect this debt.”) Failure to disclose could result in lost collections and stiff fines against the agency.  Here we might need to be a little better…how about 90%? Would 85% be OK?  What level of performance would make you jump for joy?  What level of performance would get you hoppin’ mad?  What range of performance would result in you changing nothing about your current approach?

We work with multiple collections agencies and their performance on just these two disclosures (prior to deploying our software of course!) is highly variable and all are less than 90%, despite the fact that it is a law!

Assuming you had already established specs or RCCs and you wanted to track error rates, what would you do?  If you record every call, you can use speech analytics software to “listen” to the calls and calculate an error rate. This is a workable solution but an expensive one that is not widely deployed and is thus an option for only a subset of centers.

For most centers, the only way to determine the error rate just for a point in time is to dedicate a group to listen to 50 calls with clearly defined Required Call Components and estimate the center-wide quality rate from the sample. To track this over time, you would have to repeat the process every day or every week. Fat chance. Processes are changing all the time in call centers.  If you tried to track either the error rates on process changes or on RCCs that weren’t changing, you would end up with a monitoring team larger than the size of your agent population.

Lowering the Error-Rate Once You Know It

Should you decide to wade into this murky water and try to determine the error rate for some call types, the number you come out with will likely not be too flattering. You may find yourself motivated to try to lower that error rate in which case you would have a couple options.

Call monitoring is the same as trying to “inspect in” quality in manufacturing, a practice manufacturing abandoned a long time ago (see What the Call Center Industry Can Learn from Manufacturing: Part II). Honestly, how is occasional  monitoring and occasional coaching supposed to improve error rates on the hundreds of call types some agents have to handle?  The only way monitoring can drive increased compliance is if you monitor almost every call, publicly track error rates, and dismiss agents below the 95th percentile of agent performance. This is a lot of work in and of itself, it would result in a lot of expensive turnover.  It would also create a tense work environment.

Instead of paying for a bunch of monitors to act like cops with radar guns trying to catch people doing it wrong, why not just make it easy for the agents to do it correctly?  Stealing a page from manufacturing’s playbook, centers can use error-proofing and the call center equivalent of Andon lights to make it impossible for agents to skip key steps, to track quality, and to correct any problems that do arise real time.  A range of agent-assisted automation solutions are the best practices here and with these approaches, 99.999% quality is achievable. (For more information see: Is it Time for Mass Customization of Call Centers?)  Error-free, call center quality is absolutely a reality.

Some days it seems as if there are an overwhelming number of problems in this world. But you know what? Polio isn’t one of them. It used to be a huge problem.  Then they invented a vaccine. Arguing and worrying about what level of contact center agent errors we should tolerate is a watt-less discussion because there is a way to deliver error-free performance every time.

Why [are] control limits on control chart are [sic] drawn at 3s?
Control limits on a control chart are commonly drawn at 3s from the center line because 3-sigma limits are a good balance point between two types of errors:

Type I or alpha errors occur when a point falls outside the control limits even though no special cause is operating. The result is a witch-hunt for special causes and adjustment of things here and there. The tampering usually distorts a stable process as well as wasting time and energy.
Type II or beta errors occur when you miss a special cause because the chart isn’t sensitive enough to detect it. In this case, you will go along unaware that the problem exists and thus unable to root it out.

Are there any more reasons?

The discussion goes on at great length (48 comments at the time this is written,) but I’ll just post my comment here:

Things like type I and type II errors apply to enumerative statistics. Control charts are analytic statistical tools, so these terms do not apply here. Type I and Type II errors can be stated with precision because, as enumerative statistics, inferences based on them apply to a static population. Analytic statistics, in contrast, are used to make inferences about the future performance of a dynamic process. Errors related to inferences about the future can never be precisely calculated.

That being said, the idea that tampering occurs when a process that is not being influenced by special causes of variation is changed as if it were, and that tampering makes matters worse, is certainly true. When we want to determine if a special cause is present in a process, we make use of data to help us decide. No matter what the data show, there is always a chance that we mistakenly conclude that a special cause exists (or doesn’t exist.) It’s obvious that the further a data point is from the “norm,” the smaller the probability that we’ll mistakenly conclude that a special cause is present. Shewhart did not base control limits on precise calculations of Type I or Type II error. He based them on the fact that in practice engineers at Western Electric were able to easily identify the special cause of variation when observations fell 3 or more sigma from the long term mean. They were more challenged to find a special cause for observations closer to the mean.

Think about it like this: if you created a list of everything that caused a process to change even a small amount you would have a very, very long list. You could never pin down the one big thing from this long list, because there is no one big thing. But if you ask for a list of everything that caused a process to change a lot, say by 3 sigma, that list would be relatively short. In between these two extremes are changes of intermediate magnitude and lists that vary between the long “any change list” and the short “3-sigma change list.” Just where to draw the line depends on a large number of things, such as the cost of checking out the possible causes on the list, the cost of missing something, the frequency that changes of a given magnitude occur, etc.. As a default starting point we can use 3-sigma to trigger our special cause search, if for no other reason than this has worked pretty well for 93 years. But that doesn’t mean that it should be accepted as dogma. What we are solving for are lines (control limits) that minimize total costs. In the end, it’s a management decision, hopefully one that’s based on facts and data.

No matter what your knowledge of Lean Six Sigma, come join us in a one hour lively discussion on “11 ways to Sink Your Six Sigma Project.” Master Black Belt Peter Bersbach will give an overview of each way, then open the session to a discussion on how to avoid that particular failure mode. No ideas are wrong, but we will learn different approaches we might use to avoid each of the 11 ways and have a very successful project.

1. Poor Project Selection
2. Defining Defects
3. Training Variation
4. Statistical Training
5. Shoddy Certifications
6. High Attrition Rates
7. Relying on GEMBA
8. Tool Application
9. Sustaining Results
10. Estimating Benefits
11. Six Sigma or Lean

Update 2/1/2012:
Click here to view the recording of the webinar 11 ways to sink your six sigma project. Length 44:17. This was a great webinar with a lot of input from the audience.

Update 2/8/2012:
Click here to view the recording of the webinar 11 ways to sink your six sigma project-the sequel. Length 221:48. Click here to see the chat log. This webinar covers points 8-11.