The Seven Systems of CSM Excellence

Universal practices instill high performance

What makes some companies like Intel, Southwest, and Ritz-Carlton perennial performers? Is their secret charismatic leaders? Good timing? Grand vision? No. High performance isn’t about what organizations do, but how they do it. Customer Success teams can apply the same disciplines used by top-performing companies to dramatically increase results.

Jim Collins, author of Built to Last and Good to Great, says “dynasty” companies (those generating financial returns of at least 10x for 15 years or more) behave very differently than the rest. Unlike typical organizations, top performers are fanatically disciplined, empirically creative, and productively paranoid.¹ Laser-focused and utterly relentless, they eliminate distractions and drive continuous improvement everywhere. Rather than follow industry experts or imitate others, top companies engineer their own breakthroughs using empirical evidence, observation and experimentation. And they remain hyper-vigilant, watching competitors intently and adjusting their strategies to thrive in a constantly shifting landscape.

High performing organizations like the ones Jim Collins describes depend on a set of interconnected, self-reinforcing management systems to instill their unique behaviors. Their management disciplines become embedded in the organization’s “operating system,” creating a culture of excellence in individual work areas and throughout the enterprise.  The management systems they use are universally applicable, so Customer Success leaders can use them to realize similar benefits:

Sensory System

What it does: Methodically collects and interprets customer, market, competitive, regulatory, workforce, and technology trends to continually uncover new opportunities and threats.

Leading practices: Use quantitative and qualitative analysis extensively for market and product definition and performance monitoring. Implement internal and third-party “listening posts” in multiple channels. Increase relevance and salience by interpreting findings according to market segment. Systematically analyze, review and prioritize feedback for company business reviews, product roadmaps, and process improvements. Reduce “blind spots” by periodically challenging underlying assumptions and measurement techniques.

Application in Customer Success: Collect product usage, customer satisfaction, trouble ticket, and contact frequency statistics to generate health scores for specific customers and market segments. Utilize direct customer comments in CRM records and formal customer reviews for product and process deficiencies. Share discoveries via periodic, formal feedback sessions with development, sales, marketing, accounting, and operations leaders.

Planning and Review System

What it does: Inputs information, prioritizes actions, defines objectives, goals, strategies, tactics, and owners, and aligns financial and personnel resources to promote successful execution. Evaluates progress formally and periodically, holding people accountable, adjusting plans, and promoting learning.

Leading practices: Develop strategic (multi-year) plans that articulate long-term vision, objectives and goals, customer and market dynamics, competition, product and service roadmaps, value propositions, value delivery systems, staff development, risks, and financial pro-formas. Link strategic with annual plans and implement through product development and process improvement plans. Coordinate planning and review activities via calendars, and use scenario analysis to detect and quickly respond to environmental “triggers.” Involve all employees to build commitment for action.

Application in Customer Success: Participate in enterprise planning activities, share customer intelligence and help set functional objectives, goals, strategies and tactics. Prioritize, define, implement and track account management and marketing plans along with process improvement projects. Review progress monthly and quarterly.

People System

What it does: Defines jobs, employee knowledge and skill requirements, and facilitates screening, hiring, training, performance feedback, career development and overall organizational change.

Leading practices: Define short-term and long-term staffing and skills requirements as well as succession plans aligned with the strategic plan. Use structured screening, hiring, training, retention, and cultural indoctrination practices. Conduct both formal and informal performance reviews. Interpret quantitative job performance measures in proper statistical context. Collaborate to define and hold employees accountable for development plan execution.

Application in Customer Success: Craft position plans, metrics, knowledge and skill requirements, and development plans for CSMs to build stronger relationships, deliver onboarding, and uncover and advance sales opportunities. Characterize and use personality traits, in addition to education and past experience, to screen new hires. Give regular feedback, formally and informally, and avoid ranking.

Work System

What it does: Describes requirements and designs optimal workflows at a macro and micro level between customers, business partners, suppliers, company departments and work groups.

Leading practices: Map processes to identify critical handoffs, disconnects, metrics, and process improvement opportunities. Periodically redesign processes for enhanced speed, cost effectiveness and increased quality. Protect and develop core competencies to promote strategic advantages. Use partnership management and supply chain management techniques to influence change and improvement with third parties.

Application in Customer Success: Define the customer lifecycle linking onboarding, training, engagement, renewals, upselling and cross-selling activities using phone, e-mail, video, events, webinars, and social media contact as required. Define critical handoffs and feedback loops with sales, customer support, development, and accounting.

Metrics System

What it does: Focuses managers and teams on the critical few cause-and-effect relationships that keep processes under control and promote beneficial end results.

Leading practices: Deploy and manage daily operations across the enterprise via linked, balanced and aligned dashboards. List a critical few leading and lagging indicators in each dashboard to measure key business process performance, especially attributes driving competitive distinction and financial results. Calibrate dashboard signals using customer specifications or statistical process limits. Review periodically, take corrective action, and launch process improvement projects as signals dictate.  Benchmark performance against competitors and “best in class” process references.

Application in Customer Success: Construct dashboards measuring outcomes (renewal rate, new revenue, etc.) and process factors leading to them (conformance to contact schedule, 30-day adoption %, etc.) as appropriate to the defined CSM role. Use a total of ten or fewer metrics, rolling up individual statistics into overall team performance. Set “red,” “yellow,” “green” action limits based on historical performance or goals articulated in the annual plan. Make dashboards visible in work areas, review and discuss performance with team members at least monthly.

Continuous Improvement System

What it does: Manages projects emphasizing customer focus, teamwork, and scientific methods to uncover root causes of problems, driving ongoing improvement in products, services and internal processes.

Leading practices: Execute cross-functional improvement projects using formal methods such as Lean Six Sigma, process simulations, and predictive analytics to maximize results. Choose projects based on financial or strategic impact, including major initiatives linked to annual and strategic plans. Increase effectiveness and customer value and reduce customer dissatisfaction, cycle times, and inefficiencies in all products and processes. In SaaS companies, diminish downstream bug detection, remediation, and customer churn costs through better upstream product definition, software development and validation processes.

Application in Customer Success: Implement formal methods to collect data and analyze processes to determine changes that increase customer retention and revenue and lower the Cost to Serve. Use statistical techniques such as logistic regression to study factors that impact customer churn, such as adoption rate, unresolved trouble tickets, or contact frequency. Design and execute experiments to test new ideas. Participate in company feedback loops to report software bugs and advocate for product and service enhancements.

Leadership System

What it does: Provides strategic direction, prioritizes actions, engages and inspires employees to perform at high levels, learn, and enact changes.

Leading practices: Articulate clearly and broadly communicate company mission, vision, values, goals and strategic plans. Engage the workforce and lead strategic change using formal processes. Model by example, recognize and reward high performance, and develop new leaders throughout the organization. Provide and receive performance feedback.

Application in Customer Success: Define the team’s purpose, goals and values. Understand and align with what motivates individual team members. Recognize and reward performance and hold people accountable. Incorporate leadership effectiveness feedback from superiors and employees in personal development plans.

When Customer Success leaders run their operations using the seven management systems above, their results rival the very best performers. Excellence becomes part of the culture, and customer churn, referrals and revenue relentlessly improve.

Excel-lens is a publication of Service Excellence Partners. We increase customer loyalty and business performance in the cloud computing industry. Contact us today.

Source:
1. J. Collins, M. T. Hansen, 2011. Great by Choice: Uncertainty, Chaos and Luck—Why Some Thrive Despite Them All. 

Quash the “White Space” with Four Management Tools

You contact a company trying to get a problem solved and you find yourself passed between multiple departments. While people are sympathetic, their response is, “It’s not my job.” Despite multiple voice mails and e-mails, you get nowhere. Your issue has fallen into the company’s “white space,” the cracks between the boxes on the organization chart. 

You’ve probably experienced white space issues inside your own organization, too. People perform departmental tasks smoothly, but there’s friction interacting with other groups. Processes don’t flow. Often things get “thrown over the wall,” there’s lots of finger-pointing, and it’s difficult to get things done.  

Functional silo-ism first rears its ugly head when companies reach about 40 employees. At this threshold, companies must departmentalize to increase technical capabilities and bolster management’s span of control. But priorities slowly begin to shift. Soon pleasing the boss becomes more important than making customers happy. As the firm continues to grow, functional barriers get larger and more entrenched. Left unchecked, departmental relationships can become adversarial, paralyzing new product development, service delivery, customer acquisition, and customer care efforts. 

Four tools that reduce silo-ism 

Progressive companies deploy countermeasures to mitigate the effects of white space behavior. Top organizations combine the four management practices below to substantially diminish internal friction and dramatically increase performance. 

1. Hoshin Kanri

What it is: Developed in the 1960’s at the Bridgestone Tire Company in Japan, hoshin kanri (literally translated “a bright, shiny needle”) is a rigorous, integrated system of planning, implementation, and review that points the way like a compass needle. Caterpillar, 3M, Toyota, Bosch and Danaher and many other leading companies use it. 

How it works: Senior executives collaborate to prioritize common issues, and then decide on a single breakthrough. The objective is then decomposed into a smaller set of strategies, each featuring its own executive owner and performance measure. Leaders cascade the plan throughout the organization, finally defining implementation plans at lower levels. Formal hoshin reviews then roll up progress, allowing executives to eliminate barriers that crop up. The method’s closed-loop system promotes intense focus, relentless execution, and forward momentum. 

Why it works: Unlike the common Management by Objectives (MBO) approach, hoshin aligns the organization around business, not functional, imperatives. Leaders pass these priorities down and reinforce them across the company. As a result, teams work towards enterprise-wide goals that transcend parochial concerns. 

2. Process Mapping

What it is: A time-honored technique used to study workflows, process mapping reveals the “hidden factory” behind service work. Describing the process visually helps teams identify critical handoffs, gaps, rework loops, and queues. After pinpointing improvement areas, teams can then reduce errors, speed cycle times and reduce costs. Value Stream Mapping and Customer Journey Mapping are popular variations of the method.  

How it works: Teams define process suppliers, inputs, outputs, customers, and requirements. Then they brainstorm tasks that must be completed to convert inputs into outputs, typically using Post-it® notes and butcher paper to record the workflow. Along the way, mapping participants identify improvement opportunities. 

Why it works: Mapping allows people to see the systemic nature of business—everything is connected to everything else, and what happens in one area affects all others. People quickly realize that fast, efficient, customer-pleasing workflows trump choppy, disconnected vertical structures. Top organizations assign executives to lead cross-functional, key business processes, holding them accountable for optimizing teamwork across, rather than inside, department boundaries. 

3. Enterprise Dashboards

What it is: The Japanese call an interlinked system of color-coded metrics nichijo kanri, or “daily control.” These displays help people at all levels manage the variables that lead to favorable business outcomes. Each manager’s dashboard typically monitors the key business process he or she oversees using 8-10 essential metrics that describe volume, time, cost, quality or other attributes. 

How it works: Leaders define the critical few measures that really matter by analyzing company processes, economic models, and Value Propositions. They calibrate indicators by determining ranges of acceptable values based on stakeholder requirements, process capabilities and business goals. Managers then collect data act appropriately on the signal: “green” means everything is good, “yellow” means keep an eye on it, and “red” means take immediate action. 

Why it works: With the right metrics, managers and teams focus on the most essential aspects of the job. They keep things under control and prevent downstream chaos. At top companies, executive dashboards reflect measures tied to cross-functional processes. When reward and recognition is tied to systemic improvement, managers and employees have greater incentives to work with other teams for mutual benefit. 

4. Lean Six Sigma

What it is: Lean Six Sigma is the modern integration of two proven methods: lean production and six sigma quality. Lean (a technique pioneered by Toyota in the 1970s) emphasizes speed and helps identify and eliminate wasted time, motion, and raw materials. Six Sigma (a quality method named after an imperceptibly small error rate) aligns processes with customer needs and then reduces defects and excessive variation that causes dissatisfaction. Both have been used for years in manufacturing, and the combined approach is increasingly common in service environments. 

How it works: Teams use formal methods to characterize process performance, estimate financial impact, uncover root causes of problems, design solutions, and implement changes. DMAIC (Define-Measure-Analyze-Improve-Control) or RIE (Rapid Improvement Events) provide teams with structure and statistical tools to effectively manage projects. Since teams make systemic improvements, results tend to be more dramatic and sustainable.

Why it works: Teams are often made of up representatives from all functions involved in the workflow. By working together towards common business goals, team members learn to appreciate the challenges people face in other functional areas. Besides creating more effective and efficient processes, a broader “systems view” and stronger interpersonal bonds between people promotes greater cooperation long after the project is complete. 

White space problems are a natural part of organizational development. All companies deal with it in one way or another. Fortunately, proven tools and techniques can help young companies arrest its impact and promote scalable growth. 

Cohort Analysis Done Right

Use a p-chart to properly monitor shifts in customer churn

Let's say you run a Customer Success team and your manager asks you to perform cohort analysis in order to better understand customer churn behaviors. Your customers renew on a monthly basis, and you’re interested in measuring their initial fallout rate. Using data collected over the past year, you count the number of users who canceled their subscriptions after the first 30 days and divide that number by the total number of new users during each month.¹  Your Excel spreadsheet table is shown below:

You then plot the data:

The results concern you. Although the data points vary somewhat, it appears your 30-day churn rate has been increasing all year! Using the trend line function in Excel confirms it—the first month’s churn rate has grown from about 2.2% to 3.2%!!

You share this information with your boss and she’s not happy. Clearly your Customer Success team is not doing the job. She expects immediate improvement. Or else. 

Simple, obvious... and wrong

But hold on a minute—you’ve made a serious mistake. You haven’t managed your team poorly. You’ve analyzed your data improperly!

Your error has to do with statistical sampling. Randomness occurs in all data, and experimenters must be careful to separate the “signal” from the “noise.” Statisticians warn of two types of experimental error: 

• Type 1: False Positive—a result is determined when in fact there’s only randomness 
• Type 2: False Negative—randomness is determined when in fact there’s a valid result

Without using the proper statistical methods, people can easily jump to the wrong conclusions. Overly simplified, standard tools in Excel make the situation worse. As a result, managers tend to over-react, seeing a problem that isn’t there and making changes that can do more harm than good.² Managers can also under-react, missing the cues to make changes when it’s time to do so. Most businesspeople lack a strong analytical background, so statistical errors are quite common, often leading to disastrous consequences.   

Using the p-chart

Fortunately, manufacturers have been using powerful statistical methods for years, and these practices can easily be applied in software companies. Lean Six Sigma, a quality improvement method, incorporates a broad range of tools that ensure teams properly analyze data and reach valid conclusions. You can use these techniques to your advantage. 

The control chart is a handy Lean Six Sigma tool helping managers avoid Type 1 and Type 2 errors. Control charts are used to determine if a process is in a state of statistical control, i.e., if the observed variation is due to randomness and not any particular cause. There are many different types of control charts depending on the type of data involved, but all follow the same basic structure. The p-chart (or proportion chart) uses the binomial distribution. It is the most appropriate control chart to use in this example because there are only two possibilities (the customer cancels or renews) and results are expressed as percentages.³  

The control charting procedure is as follows:

1. Determine rational subgroups. A rational subgroup is a homogeneous set of data that provides a representative sample, such as a batch of parts manufactured during a shift. Many SaaS companies define their subgroups as monthly “cohorts,” the set of new customers who sign up for software during a given month. Usually there’s nothing different about a customer who subscribes in January versus one who subscribes in February, and for the purposes of evaluating churn, it’s more accurate to use sequential, fixed sample sizes instead of varying sample sizes.⁴  In order to calculate the mean with reasonable accuracy, statisticians recommend using around 25 subgroups. In this case, we’ll choose fixed sample sizes with 168 customers in each of 24 subgroups (4032 customers/24 subgroups = 168 sample customers/subgroup).⁵  Below is your new sample set:

2. Plot the dots. As you can see, the shape looks a little different, but it still appears there’s some trending in the data. 

3. Calculate and apply the center line and control limits. 

• Compute p-bar (or average proportion) for the data set. In this example, 114 out of 4,032 customers churned after the first 30 days, a p-bar of 2.8% (114/4032). Draw this line on the chart. 
• Calculate the upper process control limit, UCL. This line shows the mean plus three standard deviations. The line is important because the probability of finding a data point more than three standard deviations away from the mean by chance is less than 1%. The UCL calculation for a p-chart is:

UCL = p-bar + 3 * Square Root {p-bar * (1 – p-bar) / n}

where n is the fixed subgroup sample size

In this example, UCL = 0.028 + 3*SQRT {0.028*(1-0.028)/168} = 0.0662 = 6.6%. Add this line to the chart.⁶  

4. Interpret the results. As you can see, most data points fall in the vicinity of p-bar and none exceed the upper process control limit, UCL. This is your first indication that observed variation is likely due to randomness and not any special causes or shifts in your process. For good measure, add lines at +/-1 and +/-2 standard deviations (probabilities of data points in these ranges 68% and 95% respectively) and add them to the chart. Mark zones “C” between the centerline and 1 standard deviation, “B” between 1 and 2 standard deviations, and “A” between 2 and 3 standard deviations from the mean as shown below.

Then apply three additional statistical tests to rule out any possibility that something is amiss:⁷ 

• Nine points in a row in Zone C or beyond on one side of the center line?—NO 
• Six points in a row steadily increasing or steadily decreasing?—NO 
• Fourteen points in a row alternating up and down?—NO 

Congratulations, you can breathe a sigh of relief! You’ve correctly established that despite appearances, there’s no trending in the data, contradicting what you originally thought. You explain to your boss that nothing has changed and results are due exclusively to randomness. The data shows that your onboarding process is in a state of statistical control and will routinely produce 30-day churn averaging about 2.8%. What’s more, you can accurately predict that 2/3 of the time future churn will be measured between 1.5% and 4%, 1/3 of the time less than 1.5% or over 5%, and only on rare occasions will it ever exceed 6.6%.  

Next steps 

You can continue to add new data points and monitor process stability using the limits you calculated above and by applying the same interpretation procedure. If any of the four statistical test results are positive, take immediate action and determine the underlying cause. You can use p-control charts to investigate customer defections at other periods of time, such as subscriptions after 60 days, 90 days, or upon annual renewal. Several Lean Six Sigma statistical packages are commercially available online (many of which are SaaS), making control charting much easier. 

Once your Customer Success process is stable, it’s possible to systematically improve it. Although keeping things under control is always your first priority, making things better is your end goal. In my next blog, I’ll describe how Lean Six Sigma methods can be used to help you improve customer retention.

Excel-lens is a publication of Service Excellence Partners. We increase customer loyalty and business performance in the cloud computing industry. Contact us today.

Notes:

1. Technically, calculating ratios when denominators vary causes an “average of the average” problem in which comparing percentages between periods introduces significant measurement error. This discussion was deleted for brevity. 
2. Human over-reaction to Type 1 errors is a fascinating subject, one with neurobiological and evolutionary explanations. It’s beyond the scope of this blog, but humans are preconditioned to see patterns and jump to the wrong conclusions, hence the need for robust application of the Scientific Method. 
3. Note that p-control charts can be used with varying sample sizes under certain circumstances (computing average n or using multiple control limits), and that other types of attribute control charts can be used for smaller sample sizes. For simplicity, this discussion was omitted.
4. Homogeneity extends to type of customer, including the market segment and associated value proposition, as described in my previous guest blog. If churn behaviors vary significantly by customer type, you should stratify your data and chart each segment separately.   
5. A rule of thumb is to choose subgroup sample sizes for attribute data such that np>5; in this case, churn is about 3%; n>5/0.03 or n>167
6. Note that in this case, the lower process control limit is negative and can be neglected; this is a “single sided” investigation where the minimum churn is 0.0% and we are interested in detecting a shift upward.
7. Montgomery, D. C. (2005), Introduction to Statistical Quality Control (5 ed.), Hoboken, New Jersey: John Wiley & Sons, ISBN 978-0-471-65631-9, OCLC 56729567

Start 2014 With New Customer Insights

Three changes to your annual customer satisfaction survey can better focus your improvement initiatives

Many organizations conduct comprehensive customer satisfaction surveys this time of year in preparation for their annual planning exercises. Surveys aid decision making for process improvement initiatives and can also be used to test new product and service ideas. But most companies miss easy opportunities to gather valuable information along the way because they fail to do three things:

1. Ask segment identification questions.

Surveys typically ask customers for demographic information (age, gender, income, location) or company-specific information (products or services purchased, account size, salesperson) to categorize and compare responses. But these questions tend to be driven by whatever is easy to measure, not by what’s most essential to know. Asking respondents to identify themselves by market segments allows companies to align their products, services, and process improvements with the benefit of greater context.

For example, let’s say a travel company identified three distinct segments in their customer base: families vacationing on school holidays, seniors enjoying their retirements, and corporate group travelers celebrating successful sales years. While all may purchase travel services, each customer set values what the company does differently: holiday availability may be more important to families, while low travel cost may be more important to retirees. The company may also determine that some customer segments are more profitable than others or represent opportunities for growth. In this example, the company could ask, “Which statement best describes you?” and offer descriptions of the three segments.

When data are analyzed according to cleanly defined segments, suddenly results have far greater strategic impact. Prioritization becomes much easier when improvements can be traced to potential top-line revenue or bottom-line profit by customer segment.

2. Ask what’s important.

Many organizations use the same survey questions they’ve always used, which allows them to track customer satisfaction changes over time. This certainly makes sense, but doing so blindly eliminates the chance to verify what’s relevant. The Importance-Satisfaction (I-S) survey technique adds the question “How important is this to you?” along with a rating scale (e.g. 1= not at all important to 5 = extremely important) to track customers’ current and changing tastes. Collecting both importance and satisfaction provides a handy measurement of the gap between the two.

High-performing organizations periodically challenge their understanding of customer preferences. After receiving the prestigious Malcolm Baldrige National Quality Award a second time in 1999, Ritz-Carlton CEO Horst Schulze remarked:

“During our implementation of the Baldrige Criteria, I’ve learned that although the sparkle of the chandeliers is important, it is not the only priority of our guests. It doesn’t matter that the petunias are perfect if the valet dents your car or your bill is wrong. We’ve learned to make our customers’ priorities our priorities… We’ve shifted from looking ‘out’ from our own perspective to looking ‘in’ from the customer’s.” ¹

Besides asking customers the right questions to determine areas of most concern, eliminating questions deemed unimportant allows organizations to make surveys shorter, which in turn increases survey response rates.

3. Analyze correctly.

Most companies use very basic calculations which can lead to the wrong conclusions. Managers typically compare average satisfaction scores from one period to the next or between one group and others. For example, if average satisfaction was 4.3 in 2012 and is 4.4 in 2013, managers often conclude satisfaction has improved 0.1. This may not be true—the determination has not accounted for experimental error, and the difference may actually be due to randomness. Student’s t or Analysis of Variance (ANOVA) is the correct approach when comparing sample means between two or more groups. Technically, if data are not normally distributed (most satisfaction data are skewed, not bell-curve shaped) or respondents select from a set of discrete ratings (e.g. categories 1-5 on a Likert Scale or 1-10 for Net Promoter Scores®), contingency tables with chi-square analysis then becomes the correct approach. To properly separate the “signal” from the “noise,” the analyst must calculate p-values to determine if differences between sample means are statistically significant.

Most executives want to understand cause-and-effect relationships and make predictions, not just make comparisons. For example, call center managers may want to know, “Which will have a greater impact on overall customer satisfaction: reducing call hold times or resolving issues on the first call?” In this case, analysts use multi-way cross-tabulation tables, but when evaluating four or more factors, the analyses are more elaborate (correspondence, classification trees, log-linear). The right methods can uncover a wide range of new insights, but managers should ask qualified statisticians for help.

Collecting customer feedback is a healthy first step for annual business planning. Adding segment identification, importance-satisfaction questions, and proper statistical analysis can then make a substantial impact on what is decided during business planning.

Excel-lens is a publication of Service Excellence Partners. Our unique approach helps founders at early stage companies better scale operations and manage growth. Contact us today.

Source:

1. James Hunt, Elaine Landry, and Jay Rao, 2000. “Case Study: The Ritz-Carlton Hotel Company, 1992 and 1999 Malcolm Baldrige Quality Award Winner,” Journal of Innovative Management, Fall 2000. GOAL/QPC.

Net Promoter Score (NPS) is a registered trademark of Fred Reichheld, Bain & Company, and Satmetrix

Remembering HP: Habitual Performance

“It’s just how we do things around here.”

I still recall the conversation between the Hewlett-Packard worker and the Tellabs manufacturing VP.  It was 1993, and we were on trip to HP’s Loveland Manufacturing Center, a key production facility in northern Colorado. Back then I sold HP test equipment in Illinois, and we were hosting a group of Tellabs executives on a benchmarking visit. My sales colleagues and I were building relationships and sharing manufacturing “best practices” with the hopes it would motivate them to buy more HP gear.

We were touring the production area and one of my customers pulled aside a passing worker, asking him about some charts hanging on the wall. The guy stopped for a few minutes and pointed to the diagrams, describing what each meant. “This one shows the count of defects by type. It looks like they were having a problem with the solder application. And over here, it looks like the adjustment dropped the defect rate by about 30%.”

A bulletin board labeled “PDCA Storyboard” prompted the interaction. A management presentation earlier in the day talked about the division’s Total Quality Management journey. HP used “Plan-Do-Check-Act” as its corporate improvement method, and the PDCA Storyboard showed the step-by-step progression. The presenter had made the bold statement that the quality practice was everywhere. It had become entrenched in the division’s operating system.

The Tellabs VP smiled and said, “So you’re saying you don’t work here but you can tell what this operation is doing?”

“Yeah. I’m on one of these quality teams in my area. We use PDCA to increase our yields, too.”

 “Come on. You’re not just a ‘plant’ walking by, an expert trying to impress us?” the executive chided him.

His response was working-man authentic. “No,” he said, shrugging. “It’s just how we do things around here.”

I could tell my customer was satisfied. He shook hands with the worker and thanked him. Without saying a word, I knew what he was thinking: It’s true. HP really is this good.

As a company HP was well respected, but it wasn’t because it was the most inventive. It didn’t come up with SPC or kanban or anything else the Tellabs executive hadn’t heard of. It wasn’t because HP only used the most advanced technology. The tour showcased some shiny, new equipment, but most was conventional and well used. It wasn’t because the company didn’t make mistakes. Over the years, the exec had dealt with the occasional HP hiccup. But where Tellabs and others would talk about fundamental change, HP would do it. And do it well.

HP had great people and great discipline. The company had a knack for studying something interesting, trying it on a small scale, refining it, rolling it out consistently, and making it all natural. Author Jim Collins calls this empirical creativity matched with fanatic discipline; direct engagement and practical experimentation followed up with utterly relentless execution in accordance with consistent aims, performance standards, and methods.¹ HP’s behavior, like other dynasty companies Collins studied, allowed it to dominate the test equipment industry for nearly seventy years.

Things have changed since 1993. The HP division became part of the Agilent Technologies spin-off, the manufacturing unit was offshored, and the HP brand has lost some of its luster since the time of “Bill and Dave.” Tellabs also changed. After heady growth, the company suffered from the telecom bubble burst; painful cutbacks, management changes, and eventual renewal as a networking products company.

I’ve changed, too. A career in sales led to marketing and operations, eventually leaving HP to start three companies and work for two more. Sparked by my time at HP, I spent many years exploring why some organizations performed consistently better than others. I learned and applied lessons in my own companies and others through the Baldrige program and the occasional consulting gig.

I’m convinced high performance boils down to simple, disciplined management systems that make people, planning, execution, and learning all more effective. It's true for organizations large and small, no matter the sector. But success always depends on great leadership and the tenacity to see it through. When excellence becomes a matter of organizational habit, long-term success is assured. 

And that’s what reminded me lately of the wisdom and discipline of a great company. Years ago they made it all happen, captured in one simple remark:

“It’s just how we do things around here.”

Footnote:

1. Collins, J. and Hansen, M. Great by Choice: Uncertainty, Chaos, and Luck--Why Some Thrive Despite Them All. Harper Business, 2011. ISBN 0062120999.

The Best Meeting Agenda

Planning is easy. Execution is hard. How can a monthly meeting keep an organization persistently on track to achieve its goals? 

Nobody likes meetings, including me. People perceive them as time-wasters. Many have gone to “no PowerPoint” talks, got rid of chairs, or eliminated meetings entirely. In my view, these are extreme measures. Meetings serve a purpose. They provide important venues to communicate, learn, and make decisions. Yes, cut back on the number of meetings, but make the ones you keep more productive. 

I think the best meeting agenda is called a Monthly Business Review (MBR). It’s a formal meeting (yes, preparation is required) designed to check progress on key plans, projects, and business performance. What makes it the best? Unlike other meetings, the MBR ensures the organization executes its business plan. The alternative, of course, is to do what most companies do: make a plan, and after a few weeks just go back to what people were doing before the planning session. 

For an MBR, all functional heads and the CEO attend. A scribe and a timekeeper are assigned. Each manager has 15 minutes and may present only three slides. During the meeting, the scribe records issues and ideas that come up on a flip chart, and unless something requires immediate resolution, the topic is parked until the review is complete. The timekeeper also plays an important role. He or she prods managers to stay on topic lest the MBR lose focus and become interminably long. Here’s the agenda: 

• Welcome and Opening Remarks (CEO, 5 minutes) 
• Company-wide Dashboard Review (CEO, 10 minutes) 
• Functional Round-Robin (15 minutes each VP): 
• Dashboard Review
• Updates
• Successes
• Needs
• Hoshin Review (15 minutes for each strategy owner)
• Action Items (15 minutes)
• Other Items/Wrap-Up/Schedule Next Review (10 minutes) 

The first essential element is the dashboard, consisting of the top ten metrics at the enterprise level and for each function. The company-wide dashboard may list things like revenue, expenses and customer satisfaction, whereas the marketing dashboard may include impressions, web visits, and lead conversion rate. Each measure is color-coded: green says everything is going well, yellow indicates things may be going off track, and red means take immediate action. Red signals get special attention; the manager describes the problem’s root causes and the actions being taken. Dashboards show cause-and-effect relationships, allowing managers to view the organization as a living system. The review also keeps managers focused on keeping the fundamentals under control. It provides context for decision making; if a new idea or initiative doesn't positively impact a key metric, it’s probably not that important. 

The second essential element is the Hoshin Review. Hoshin kanri, a Japanese breakthrough improvement method, is an incredibly powerful tool for driving organizational alignment and change. During annual planning, the executive team collaboratively defines a mission-critical, breakthrough objective, along with supporting strategies, owners, and performance targets. An example hoshin objective may be, “Transform the sales process from a direct to a channel marketing and sales model” with goals to “increase annual revenue by 3x and reduce customer acquisition cost by 50%.” The objective is broken down into 3-5 major strategies and goals, such as “Recruit, contract, and implement third-party marketing relationships; goal of 3 by June 1.” Assigned strategy owners then form cross-functional teams and develop implementation plans. During the MBR, the Hoshin Review checks status, surfaces and removes any barriers to execution. 

Order is important: business fundamentals before hoshins. Why? If the basics are out of control, working on more advanced initiatives makes no sense. Make sure the foundation is solid prior to reaching for the breakthrough. 

Towards the end of the session, the scribe reviews any issues or ideas surfaced on the flip chart during the meeting, distilling them into action items, owners, and deadlines. Any outstanding action items from previous meetings not already addressed are also checked to make sure nothing falls through the cracks. 

Obviously some meeting preparation is involved. Functional leaders meet with their teams in advance, rolling up data, interpreting signals, and planning actions for their dashboard metrics. Hoshin strategy leaders check progress on their project plans. The CEO must also prepare. He or she must review the top-level, enterprise-wide metrics and be ready to help executives prioritize next steps. 

Work behind the scenes is also important. If the CEO notices chronic red signals or sluggish execution on hoshin strategies, he or she should meet separately with executives for 1-on-1 coaching sessions. Accountability for progress and results is important to maintain, but CEOs should avoid calling out individual struggles during the actual review. 

So what do you think? If you had to arrange a meeting, wouldn't an MBR be one of the most valuable? If the goal is moving the organization forward, perhaps there’s no better agenda.