Business Improvement – Put on Your 3D Glasses

Many CIO’s from top performing organizations say their  ability to impact the success of the business hinged on their having personal experience in Operations in addition to their knowledge of Information Technology.

It is not enough to just have IT and Operations people on the team. They also need to be able to see and understand things from each other’s perspective in order to maximize each other’s strengths.

Make sure everyone has their business and technology glasses on to see the clearest path to improvement.

Project Failure - Just Set It and Forget It

Improvement projects are always at risk for project slip and subsequent failure. It is necessary to be tenacious about communication and countermeasures to prevent. One of the most dangerous times is after initial release of new tools, software, or processes. Communication and feedback are most critical here. It is often easier for people to slip back to the old way than pick up something new – even if you perceive the new way as being easier. Don’t just walk away, even if it looks like a slam dunk.

There are two ways that resistance to the new process show up:

1. Vocal communication
2. Silent death

In the case of vocal communication, make sure to pay close attention to the concerns being voiced. They may sound like complaints, but they are really the ticket to success. If you can address their legitimate concerns, people will hop on board and bring others with them.

If all things are quiet with a lack of feedback or communication, proactively look closely for the presence of warning signs. Hesitating to uncover silent concerns and put countermeasures in place quickly will drastically reduce the momentum needed to get the best result. That is how so many corporate initiatives become “just another corporate initiative”.

Problems with off-the-shelf Lean Learning Tools

Creating Lean learning tools for a mass public almost goes against the principles of learning through development. It is very difficult to find the simplest starting point for a learning tool that is applicable to the widest audience. The best learning tools break the concept down to the simplest form in the context that it will be applied - and using local terminology. No two organizations are alike so the conditions are always going to be different. For this reason, the learning experience will not reach its full potential with off-the-shelf learning tools.

Production Pacing Indicator Example

Even a simple display, like the one above, of a target vs. actual production count with red/yellow/green color indicators raises numerous questions:

• should pausing the elapsed time be allowed (like for during breaks and lunch)
• if paused, should it recalculate target based on total running time only
• should stopping automatically clear the display or retain it until restarted?
• should the counts restart every hour or be cumulative?
• what should be used as a target: pcs/hour, pcs/shift, pcs/day
• should the target rate be fixed, or allow adjustment throughout the shift?
• how often should the display update?
• should the color change be based on mathematical rounding of the target/actual calculation?
• Should it round up or down?
• Should it display the actual percentage to target or just the colors?

As the participants surface these questions relative to the decisions that were made in creating the off-the-shelf tool, it will do two things:

1. the participant’s learning or application of the learning may be inhibited by their experience with the tool and its “limitations”.
2. participants may question the validity of the tool because they see more “problems” with it, than benefits.

Do any of the following sound familiar?

• “It doesn’t do this…”
• “It doesn’t do that…”
• “It won’t work here, because…”
• “How does it handle this situation?”
• “Can you do that with it?”

Statements like those above distract the participants from the learning experience.

The best tools for learning are the ones that are created and customized specifically at the point of use, in collaboration with and for the participants engaged in the experience.

Group Agreement vs. Executive Order in Moving Initiatives Forward

Executives have the job of setting the strategies and objectives for an organization to meet/exceed their corporate goals. The managers and front line people further down the organizational hierarchy are responsible for making it actually happen.

• Can an organization move forward with only an executive directive? Sure, some can.
• Will it be as effective without group agreement? Not likely.

The less group agreement you have, the more likely the initiative will be point optimized in each of the organization’s vertical silos. The maximum effectiveness is achieved when the optimization takes place horizontally across departmental or functional boundaries. Group agreement is fundamental to that process.

You Might Have the Wrong Plan If…

You might have the wrong plan or approach to solving a problem if:

• The leader or project owner comes into the problem solving meeting with a list of action items already formulated and starts delegating them to the “participants” in the meeting.
• People are talking negatively about the plan in their cubicles or around the water cooler and no one is stepping out as a spokesperson for why it is the right plan/approach.
• Groups of people are openly showing resistance to change.
• The attendance at the status meetings declines every time the group meets.

You are on the right track to a good plan if:

• People eagerly start listing activities that need to be accomplished and volunteer to take care of them (following through).
• People in the participant group are heading off resistance from others without escalation to the project owner or leadership.
• People have a sense of pride and ownership of the process they have a hand in crafting.

This is most applicable when the problem at hand crosses departmental and/or geographic boundaries and would be best solved using true employee involvement from a cross-disciplinary team.

* I’m obviously not an artist so please cut me some slack on the cartoon.

Using Data to Refine Perception

If you find yourself saying the following:

I don’t need to spend time putting a measurement system in place to tell me what I already know. I’m living the issues every day. I know where the problems are and what to do to fix them.

You might be in a situation where perhaps you should reconsider your position. Sometimes it is necessary to collect data for other reasons - like convincing others.

Three indicators that investing time collecting data might be worth the investment:

1. People say they agree with you about what the problems are and what needs to be done to fix them, but their actions are to the contrary. [persuasion via demonstration]
2. When the same problems keep recurring despite having a process or countermeasures in place to prevent them. [verification]
3. Other problems keep getting all the attention and resources from the leaders and your peers, despite your recommendations or insistence otherwise. [proportional prioritization – magnitude/scale]

Perception is reality. Data is an effective tool to influence perception in order to provide an opportunity to improve the reality.

* Note: Statistics can be [mis]used or misunderstood to support almost any theory like the relationship between shark bites and ice cream sales. I don’t mean for you to use data in a deceptive way just to influence others to support your position. Make sure the data and your understanding of the situation match - checks and balances.

Pattern-Based Process Improvement

Pattern-based process improvement is a practical method of making improvements where an exhaustive analysis and re-engineering exercise is prohibitive. The process consists of looking for patterns to identify key characteristics of a process that might provide valuable insight about opportunities to improve the process. A prerequisite to finding patterns is having data or information available for review.

Real world example

Objective: Improve how parts are scheduled across manufacturing work centers to reduce late orders and unnecessary expediting.

Background: A supervisor of a manufacturing facility schedules orders on a number of similar manufacturing work cells. He normally uses the following information to create the schedule based on his experience, a few rules of thumb, and some light calculations:

• order due date
• current schedule of orders on the work cells (capacity vs. loading)
• change-over time (the  time it takes to change the machine to accommodate a different component part or assembly)
• order quantity
• estimated production time (time it takes to process the parts through the work cell)
• physical size and shape of the part on order

Method: The supervisor uses intuition based on a large number of observations to make decisions (Bayesian statistics) when creating the schedule. The idea behind pattern-based process improvement is to begin to quantitatively blend the supervisors experiential knowledge and Bayesian intuition with the data to create standard work that improves the predictability of the scheduling process.

Start by looking at the historical data about how the work cells were scheduled in the past. This method works best when the data is in a spreadsheet or database so the data can be looked at from several angles. Sort and group the data multiple ways looking for patterns or trends – good and bad. How much you can learn from the exercise depends on how much information is available and how valuable that information is. For example:

• Are there part sizes or size ranges that are commonly scheduled on certain work cells more than others?
• Are there work cells that have more downtime, more change-over time, more schedule changes, or expedites?
• Is there a pattern to size vs. quantity or quantity vs. work cell?

If you can find a desirable pattern or a trend, determine if it is possible to create a rule that would make the pattern a more consistent part of the standard scheduling process. If the pattern is associated with a negative result, determine if there is a way to detect the pattern early, or eliminate its presence completely. It is important when using pattern-based process improvement, the output of the process is monitored carefully to fully understand the effects of the change. Sometimes changes introduce new issues. This should be looked at as an iterative improvement process, not a “set it and forget it” tactic.