The Data Heads

Dr. Neil Polhemus, CTO at StatPoint Technologies (and publisher of StatGraphics) contributed a great article in the current issue of Quality Magazine about selecting statistical software for Six Sigma. In it he lists four criteria for selecting the right statistical package:

1. How strong a background in statistics does the typical operator have?
2. What types of data are operators most likely to encounter?
3. If data are mined for information, how easily can multiple approaches with multiple options be tried?
4. How easy is it to create a report or presentation that can be shared with other colleagues?

I’ll answer each of these questions for GainSeeker Suite before the end of this post, but first I want to surface an unspoken assumption in the article and add a couple of criteria that I think Dr. Polhemus missed in his list.

The unspoken assumption is that one statistical package will serve all the needs of a Six Sigma deployment. My experience is that there are at least two broad categories of statistical software, and each has their place in Six Sigma.

Two Categories of Statistical Software

One category of statistical software is Advanced Statistical Analysis tools. Dr. Polhemus’ article outlines criteria for this group. Products in this category include StatGraphics, Minitab, JMP and others. These systems were developed (originally) for statisticians. Often Black Belts (BBs) and Master Black Belts (MBBs) depend on these packages for in-depth work in the Analysis phase. These systems are less useful for selecting projects. For the most part they operate poorly in the Control Phase. Put another way, these tools are of less use to the Champions and Business leaders who charter projects, and also of less use to Green Belts (GBs) and Process Owners who inherit and live with a project when it is completed.

The other category of statistical software is what I call Real-time Enterprise SPC Solutions. It will come as no surprise that GainSeeker Suite falls into this second group. This category comes out of the Real-Time Statistical Process Control (SPC) world. These packages are designed for ongoing data collection and analysis in a continuous improvement (kaizen) environment. These tools are, first and foremost, a tool for process owners and Green Belts. They are also tools for Champions and Sponsors (business leaders) who are chartering projects and driving business performance.

While there is some overlap between the two categories, they are more complimentary than competitive. In fact, they should readily share data. Data should be especially portable from a Real-time Enterprise SPC solution to the Advanced Statistics Solution. That way BBs and MBBs can readily tap into the enterprise data sources to support their efforts.

So here are the additional criteria that you should look for when you’re selecting a Real-time Enterprise SPC System.

Criteria 5: What does it take to get new data into the system?

Advanced Statistical Analysis Packages begin with an assumption that data are in a file, in rows and columns. In this view, data are static: generated once, analyzed in some way and then saved in a folder somewhere. Real-Time Enterprise SPC Packages assume that we are tapping into a live stream of data. Each new data point contributes to our understanding of the process. (Some of the Advanced Stats Packages are beginning to recognize this, but their core competency is in analyzing a static data set.)

The ability to readily incorporate new data is what makes Real-time Enterprise software so effective in the Control Phase. Users set up automatic data collection once and then monitor the results for exceptions.

Keep in mind too that the system should collect data at all levels of the organization. Good systems will make it easy to collect and manage data from the shop floor to the executive suite. This makes it easy to capture high levels of business metrics which can be used to help prioritize projects.

When selecting a statistical package, be sure to ask:

• Can the system tap into any data source, including front-line process owners, gages, a wide variety of text files and databases, PLCs, PDAs, cell phones, and so forth?
• Can the data entry process be controlled so that only valid data can be entered into the system, in a reliable and repeatable way?
• Can data be collected automatically and without human intervention?
• Is it easy to set up and manage these data collection processes to meet all the various needs across my business?

Criteria 6: Does the system automatically test new data for real-time process shifts?

Real-time doesn’t just refer to the process of connecting to data sources and readily incorporating new data. It also refers to statistically evaluating all new data for expected variation. This is an essential tool for understanding processes. If the system does detect a change or shift, it needs to automatically communicate that to people and systems that can do something about it.

When selecting a statistical package, be sure to ask:

• Does the system automatically detect process changes using appropriate statistical tools?
• Does the system automatically let me know there is a shift through email, pagers, on-screen displays, or other appropriate means?

Criteria 7: Are Data Stored in a Robust Relational Database?

The word “Enterprise” in our category name (Real-time Enterprise SPC Solutions) tells us that we’re not looking for a point solution. There are some fine packages out there that do SPC with Excel spreadsheets. But these programs can create a data management nightmare when you are managing all the data in your business (not to mention the risk of defects being introduced in a spreadsheet environment).

An enterprise system builds a data warehouse in a relational database. This makes it possible to tap into a rich data set for selecting and prioritizing new projects. It also makes it easier to share data (and best practices) across the organization.

When selecting a statistical package, be sure to ask:

• Are data stored in a robust relational database structure with a flexible hierarchy?
• How fast are retrievals on large data sets?
• How easy is it to group or segment data?

Criteria 8: How Easy is it to Slice and Dice the Data?

A good Real-time Enterprise SPC System will collect data at multiple levels of the organization. It shouldn’t be confined to the down and dirty shopfloor data.

By capturing this data – along with information about the data – think of it as demographic information – you can slice and dice the data to find opportunities to improve the system.

At high levels it might mean viewing Overall Equipment Effectiveness (OEE) by Line, and then drilling down into various machines or sliced across all shifts. In a transactional environment it might mean tracking cycle times across all offices, or within offices by customer service rep. Being able to easily slice and dice the data makes it easier to understand the relationship of all the parts.

When selecting a statistical package, be sure to ask:

• How easy is it to drill into various subsets of the data?
• Are automatic analysis wizards available to help prioritize and focus your attention on the critical variables?
• Can you data be rolled up into dashboards and other high level summary views for easy monitoring?
• Can data be easily tagged with demographic information?

These additional four criteria are a good starting point for rounding out your tool box of statistical software for Six Sigma.

Additional information

For more information, check out these white papers and case studies:

• Freeing Six Sigma from the ‘Data Shuffle’
• Data grouping and drill down
• Walking the talk – How Micropump built a comprehensive data system to empower their people with data
• Aberdeen Lean Six Sigma Benchmark Report
• The Role of Real-Time Data in Improving Profitability and Customer Satisfaction
• Building a Six Sigma Measurement System in Financial Services

How GainSeeker performs against Dr. Polhemus’ criteria

I promised at the start of this post that I’d address how GainSeeker Suite performs against Dr. Polhemus’ criteria.

1. How strong a background in statistics does the typical operator have?

GainSeeker Suite serves a wide population of users, and assumes that the typical user has little or no background in statistics. Furthermore the system assumes that the user has many other tasks to perform besides statistical analysis.

2. What types of data are operators most likely to encounter?

GainSeeker Suite is targeted for engineering and manufacturing applications. The product is in use in some purely transactional environments too. The system isn’t particularly robust for managing survey data, but does very well with cycle times and defect/error tracking. The system is not designed for the R&D community.

3. If data are mined for information, how easily can multiple approaches with multiple options be tried?

GainSeeker is an interactive system. Users do not need to write programs that are submitted for execution. Having said that, it is not intended to function as an advanced statistical tool. Instead it readily ports data to other software systems including advanced statistics packages. Of course Gainseeker is an excellent tool for automatically updating databases and analysis.

4. How easy is it to create a report or presentation that can be shared with other colleagues?

GainSeeker pays particular attention to sharing data, analysis and reports with various user communities. Users can access data over the web, including mobile devices, and output can readily be delivered by email. In addition, GainSeeker includes a new Enterprise Dashboard module that provides easy-to-understand role-based summary knowledge.

What do you think? Are there other Critical to Quality Characteristics that we haven’t mentioned?

Yesterday the ASQ (American Society for Quality) issued their Quarterly Quality Report for December 2008. If you haven’t read it already, I encourage you to take a look. Based on a survey of only 47 persons, you have to wonder about how far you can take the conclusions, but I found the findings helpful.

Over 75 percent of the respondents were seeing specific responses to the economic downturn. These include reduction in force, reduction in training efforts, a reduction in budget for quality activities, and backing away from quality initiatives. This was in line with what I expected.

I was surprised, however, to see that when presented with a list of negatives, 20% of these respondents wrote in more positive responses. These include:

a noticeably increased emphasis on quality, especially in the area of preventive action; an increase in continuous improvement activities designed to provide competitive advantage; concerted efforts not to cut back, but rather improve and add programs and take a sharper focus on quality now; and also an increased desire to use quality improvement activities to reduce expenses.

This seems to be what lead the authors to conclude:

Quality practitioners say that over the past year they were more likely to have more opportunity rather than less opportunity to become involved in business development activities (such as new product development, establishing business strategy, meeting with customers, and working with sales and marketing). Perhaps this means there is some hollowing out among the quality troops – fewer people and less budget – but not necessarily a shrinking in the size or ambitiousness of their quality programs in a strategic sense. They still have big ambitions, but they’re forced to do more with less.

The survey asked how the downturn is impacting what people are paying attention to. Not surprisingly, ‘Cost Cutting’ ranked at the top and ‘Growth Through Acquisition’ ranked at the bottom. The question for me is how will cost cutting be achieved? If through downsizing, then quality staff should be concerned; if through Becoming More Efficient or Waste Reduction, then there may be hope.

The proof may be in one of the statistics presented near the end of the report. I was disappointed to see once again the gulf between the quality professionals and their leaders. Nearly 80% of the quality pros believe their profession confers a competitive advantage, while only 34% of top management agree.

With that kind of gap it’s going to be hard to connect quality efforts to top management’s interests.

The report concludes that organizations are reacting in fundamentally different ways to the economic challenges:

On the one hand are those going into crisis mode, cutting back and de-emphasizing quality initiatives. On the other hand are those that continue to invest in quality and innovation as a competitive advantage even in the face of economic uncertainty… Organizations that refuse to panic, that move ahead judiciously with new initiatives, and that don’t cut too deeply will be better positioned to excel when the economy rebounds.

So far our experience is that Hertzler Systems is connecting with this latter group. Our customers continue to see opportunities to invest in real-time data to help reduce costs, improve efficiencies, reduce waste, and incrementally improve existing processes and products. We’re especially finding that asset utilization and Overall Equipment Effectiveness (OEE) are valuable. We’ve been able to support our customer’s intent to pay more attention to these issues.

But what is your experience? How well are you aligned with your leadership? Or if you’re in leadership, how well are staff lined up with you?

A recent study by the Aberdeen Group found that Best-in-Class manufacturers substantially out-perform laggards.

Duh… Of course Best-in-Class have higher yields, throughput, and profits, and are more likely to deliver product on time. Here are the stats:

What we wanted to know is why. Why do Best-in-Class performers enjoy profits that are 25% higher than Laggards? What do they do that is different? How do they get those kinds of significant differences?

The Aberdeen Report, available here, gives a good start to answering these questions.

As a Data Head, I wasn’t entirely satisfied until I had sliced and diced the data myself. Specifically I needed to see the relative importance of the various components of good performance. What I found surprised me and opened new layers of meaning to the Aberdeen Research.

Based on this add-on research, I wrote a companion White Paper that I hope you’ll download and read: “The Role of Real-Time Data in Improving Profits and Customer Satisfaction“.

Take a look at both of these reports. Then share your comments: how do these findings fit with your experience?

The other day I was showing a colleague the Data Cost / Value Matrix and describing the four aspects of data value.

He made a comment that got me thinking. I was explaining the fourth aspect of data value: Data Visibility and Transparency when he said: “For my customers, transparency isn’t the key issue. The biggest issue is that they are drowning in data they can’t use. If you can make the data they already have more usable then you’re providing value.”

My first impulse is that perhaps I need to relabel the graphic so that “Data Visibility & Transparency” reads “Data Visibility and Usability.”

The more I thought about it, however, the more I realized that all four aspects of data value have to do with making data more usable.

Product Release and Control is the minimal, entry level approach to making data more usable. Data for product release and control validates that our products are acceptable for shipment. It may be accept/reject type data, and may be based on either measurements or some other kind of pass/fail criteria, and is based on the voice of the customer. Product release and control is necessary, but not sufficient.

Process Control makes data more usable because we’re relying on statistical theory to help us understand when we should react and when we should leave things alone. Process Control empowers us to react immediately to instability and unexpected variation.

Using data for Continuous Process Improvement makes the data even more usable. When you can close the loop on processes and drive continuous improvement, you get significant returns on your efforts. Closing the loop means being able to find hidden sources of variation and correlation between key input and key output variables.

The last aspect – Data Visibility & Transparency – adds value because when data is readily visible across all levels in an organization, it changes the way people work. One engineer put it to me this way:

The real time part of it has been cool. I have walked into several meetings and said “As of 5 minutes ago, this week our first pass yield is 93%.”

In the past I would walk into a meeting and report on week-old data. So inevitably there would be questions on “Do we have this fixed?” and the answer would be “I think so.”

We are definitely making a lot more decisions based on data rather than gut feel or incomplete data. We feel like we are getting the entire landscape before we go down and make a decision on what we are going to do.

We’ve been getting some good press recently for some work we’ve been doing with a well know foods company. This project implemented a real-time Overall Equipment Effectiveness (OEE) dashboard so they could collect and report on Key Process Indicators (KPIs).

As the project manager states, “The Hertzler System’s color-coded and real-time display of production line performance has given our operators a heightened sense of ownership over the plant’s performance. Rather than analyze performance reports the next day, employees can act on real-time data from the performance boards, leading to faster issue resolution and better overall performance. Furthermore, this system will allow us to maintain a historical record of our performance, which will guide our long-term improvement efforts.”

This project actually began several years ago when we began collecting package weight data from check weighers on the production line. The company used this data to help reduce overpack and save money.

With that success under our belts, they asked us to help them collect downtime and other data associated with OEE, and to display these Key Process Indicators (KPIs) automatically on flat panel displays on the factory floor.

Corporate had mandated that they get this information out to the workforce, and they were manually updating white boards with markers at the end of each shift. It was a time consuming, error-ridden process.

Here is a picture we took from inside the plant showing the shop floor data collection station, with the large flat panel display suspended from the ceiling.

And here is a screen capture of the OEE Dashboard display. This was custom-developed for this customer and combines data from a variety of sources. The column labeled Downtime Reason scrolls to show all of the reasons for downtime during a particular hour.

Research shows that real-time data is one of the key strategies that differentiates Best-in-Class performers. You can read more about that research in this Aberdeen Report on Event Driven Manufacturing Intelligence and in our accompanying white paper on the The Role of Real-Time Data in Improving Profitability and Customer Satisfaction.

A couple weeks ago I published an audio interview with Jay Bronec about his ‘Ah-Ha’ Moment when he realized that he was spending valuable company time doing non-value-added work. In that interview he described how he is automating his company’s (QualiFine) KPIs by integrating our CRM and Web data using GainSeeker.

Today I followed up with him to see how that project was coming. He took me on a webex tour of his project and I was impressed. He is using GainSeeker Suite to mine data and analyze his target market. Then he ports that over to Minitab for some advanced regression analysis that predicts class size based on how many people have registered for the class and how many days are left to sign people up. It is very cool.

But after we talked for a while, I turned on the tape recorder and asked him a question:

“Jay, whats the value you’re offering your customers? Why does it matter to people if they implement GainSeeker and get training in an economy like we have today? Why would anybody want to spend money on that today when things are crashing around us?”

For a little over seven minutes we discuss the Data Cost / Data Value Matrix and how it applies to saving money in an uncertain economy. We touch on dashboards, CMM (Coordination Measuring Machine) data collection, and how real-time data can catch problems before you waste a day’s production.

Follow this link to hear some great insights into the value of real-time automated data.

This morning I opened my weekly update from LinkedIn and saw the following note: Jay Bronec is working on automating QualiFine’s KPIs by integrating our CRM and Web data using GainSeeker.

I fired off an email and asked Jay to fill me in. He called my a few minutes later from his car. In the middle of the conversation I turned on the tape recorder so you could hear Jay explain how he is automating KPIs using GainSeeker SPC Software.

Jay’s company, QualiFine, is the largest independent Minitab training program in the country. He is also an independent regional representative for our GainSeeker Suite. QualiFine is aligned with Hertzler Systems because Jay wants to help his customers reduce the cost and improve the value of the data they have in their organization.

In this podcast Jay describes his “A-Ha” moment when he realized that he is no different than his customers: his current data collection system is unsustainable and unable to help him make good business decisions.

The other thing that you’ll hear is a connection to Mike Webb’s vision of sales process improvement. Mike has a blog called Six Sigma Selling, and in it he draws the parallels between selling and manufacturing processes. For example, if you provide sales people with better raw materials you’ll have a better close rate. If Jay is successful with his KPIs he’ll learn a lot about his ‘raw materials’.

I’m attending the Aberdeen Manufacturing Executive Summit today and tomorrow. The speakers have been great, but I’m intrigued by the live surveys that they’re running between speakers. This morning they asked two questions back-to-back and the results shocked me.

The first question was “How is the macro-economic picture affecting your budget?” I wasn’t surprised to see that only 9% of the people at the conference were forecasting increased budgets. The rest expected no change (31%), Frozen (14%) or Decrease (34%). (I’m afraid I’m not sure about the difference between No Change and Frozen.)

The second question was the one that jarred me: “How is the macro-economic climate affecting your growth strategy?” The results were a complete flip-flop. (Well the survey is being held on election day.)

Sixty-eight percent planned expansion, while only 6% planned contraction. The balance (26%) are staying the course.

Grow your business with fewer resources.

Do more with less!

What is clear from our experience, and is now supported by research from the Aberdeen Group, is that one of the best ways to do more with less is to empower your people with ready access to accurate, actionable, real-time data.

You can download a free copy of the Aberdeen Report on Event Driven Manufacturing Intelligence, along with our companion white paper on the Role of Real-time Data in Improving Profitability and Customer Satisfaction from the Portfolio section our website.

Real-time data helps you respond to problems faster and reduce material costs and scrap and rework costs, and it frees staff for more productive work.

That’s doing more with less.

Recently a colleague forwarded this email from a friend of his and asked me for my comments:

Please let me know what lean/6sigma book you would recommend. I’ve read a couple over the years but they are a bit dull and won’t fire up our management – is there one that is simple but convincing?

You’d be surprised how hard it is to get their heads out of the sand. Part of the problem is that we are so successful and dominant in our field.

e.g. At a major meeting last week, the exec responsible for customer satisfaction presented data to show that our competitor is the leader in terms of quality and customer satisfaction. He actually said “we don’t want to copy THEM because their margin is lower than ours so their quality is costing them money”. That’s how dumb and simplistic we are.

My response:

The problem you’re facing is way too common, and I don’t think there is any pill you can give your CEO to adjust his attitude. This isn’t what you want to hear, but until your CEO’s hair is on fire, I don’t think there is any book that will make a difference.

If you can find some smoke somewhere above the hairline, and then tie that back to quality and customer satisfaction, you might get somewhere. Sadly there is usually a huge disconnect between the ceo/finance function and quality/performance. Here is an true example:

I’ve been working with a customer (an electronics firm) on a data collection/analysis project. A bright Six Sigma Black Belt proved a direct correlation between the statistically significant variation on a handful of test results and out-of-box failures at the customer’s site. These were units that met specifications on well over a thousand tests, but still failed out of the box. Those OOB failures were threatening the contract: the customer was ready to pull the business.

We put together a proposal using SPC software to capture the signals so engineers would know immediately when they had a unit that was statistically different than the others (even though it still passed all the tests). It was a beautiful solution and everyone was really excited about it.

To sell that proposal to upper management my contact bypassed the (to me) obvious argument that identifing statistically significant variation would isolate defective units, which protects the customer from receiving bad product, thereby saving the contract.

(I can hear all the MBBs in the audience saying I’m not really using statistics right, but they were doing 100% testing here so pardon me.)

Instead my contact framed the proposal around faster product release cycles and the impact that would have on inventory turns. By having real-time data as the units were produced, he argued that they would be able to release production lots from WIP to Inventory 3 or 4 hours earlier. That was an argument that got the finance guy and the CEO excited.

I tell this story because it is an example of how a creative (read politically savvy) middle manager pushed through his agenda for quality process improvement using language that any  CEO understands. No book on SS or TQM or anything else would accomplish the same thing.

So look for smoke above the hairline. Something is keeping your CEO awake at night, and unless it is his girlfriend, you can probably tie it back to quality and customer sat.

Hope that helps, and best wishes.

Regards,

Evan

Even though the CEO and CFO didn’t care, in the first 10 days of the pilot project, GainSeeker real-time SPC software trapped two defects that the test process couldn’t catch. My contact reported: “Three defects in a year is enough to knock us out of ‘Preferred Vendor’ status. Anytime I stop two defects from getting to this customer, I’m a happy man.”