What Sub-Metering did for Nissan in Tennessee

When Nissan built its motor manufacturing plant in Smyrna 30 years ago, the 5.9 million square-foot factory employing over 8,000 people was state of art. After the 2005 hurricane season sky-rocketed energy prices, the energy team looked beyond efficient lighting at the more important aspect of utility usage in the plant itself. Let’s examine how they went about sub-metering and what it gained for them.

The Nissan energy team faced three challenges as they began their study. They had a rudimentary high-level data collection system (NEMAC) that was so primitive they had to transfer the data to spread-sheets to analyse it. To compound this, the engineering staff were focused on the priority of getting cars faster through the line. Finally, they faced the daunting task of making modifications to reticulation systems without affecting manufacturing throughput. But where to start?

The energy team chose the route of collaboration with assembly and maintenance people as they began the initial phase of tracking down existing meters and detecting gaps. They installed most additional equipment during normal service outages. Exceptions were treated as minor jobs to be done when convenient. Their next step was to connect the additional meters to their ageing NEMAC, and learn how to use it properly for the first time.

Although this was a cranky solution, it had the advantage of not calling for additional funding which would have caused delays. However operations personnel were concerned that energy-saving shutdowns between shifts and over weekends could cause false starts. ?We’ve already squeezed the lemon dry,? they seemed to say. ?What makes you think there?s more to come??

The energy team had a lucky break when they stumbled into an opportunity to prove their point early into implementation. They spotted a four-hourly power consumption spike they knew was worth examining. They traced this to an air dryer that was set to cyclical operation because it lacked a dew-point sensor. The company recovered the $1,500 this cost to fix, in an amazing 6 weeks.

Suitably encouraged and now supported by the operating and maintenance departments, the Smyrna energy team expanded their project to empower operating staff to adjust production schedules to optimise energy use, and maintenance staff to detect machines that were running without output value. The ongoing savings are significant and levels of shop floor staff motivation are higher.

Let’s leave the final word to the energy team facilitator who says, ?The only disadvantage of sub-metering is that now we can’t imagine doing without it.?

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What Kanban can do for Call Centre Response Times

When a Toyota industrial engineer named Taiichi Ohno was investigating ways to optimise production material stocks in 1953, it struck him that supermarkets already had the key. Their customers purchased food and groceries on a just-in-time basis, because they trusted continuity of supply. This enabled stores to predict demand, and ensure their suppliers kept the shelves full.

The Kanban system that Taiichi Ohno implemented included a labelling system. His Kanban tickets recorded details of the factory order, the delivery destination, and the process intended for the materials. Since then, Ohno?s system has helped in many other applications, especially where customer demand may be unpredictable.

Optimising Workflow in Call Centres
Optimising workflow in call centres involves aiming to have an agent pick up an incoming call within a few rings and deal with it effectively. Were this to be the case we would truly have a just-in-time business, in which operators arrived and left their stations according to customer demand. For this to be possible, we would need to standardise performance across the call centre team. Moving optimistically in that direction we would should do these three things:

  • Make our call centre operation nimble
  • Reduce the average time to handle calls
  • Decide an average time to answer callers

When we have done that, we are in a position to apply these norms to fluctuating call frequencies, and introduce ?kanbanned? call centre operators.

Making Call Centre Operations Nimble
The best place to start is to ask the operators and support staff what they think. Back in the 1960?s Robert Townsend of Avis Cars famously said, ?ask the people ? they know where the wheels are squeaking? and that is as true as ever.

  1. Begin by asking technical support about downtime frequencies, duration, and causes. Given the cost of labour and frustrated callers, we should have the fastest and most reliable telecoms and computer equipment we can find.
  1. Then invest in training and retraining operators, and making sure the pop-up screens are valuable, valid, and useful. They cannot do their job without this information, and it must be at least as tech-savvy as their average callers are.
  1. Finally, spruce up the call centre with more than a lick of paint to awaken a sense of enthusiasm and pride. Find time for occasional team builds and fun during breaks. Tele-operators have a difficult job. Make theirs fun!

Reducing Average Time to Handle Calls
Average length of contact is probably our most important metric. We should beware of shortening this at the cost of quality of interaction. To calculate it, use this formula:

Total Work Time + Total Hold Time + Total Post Call Time

Divided By

Total Calls Handled in that Period

Share recordings of great calls that highlight how your best operators work. Encourage role-play during training sessions so people learn by doing. Publish your average call-handling time statistics. Encourage individual operators to track how they are doing against these numbers. Make sure your customer information is up to date. While they must confirm core data, limit this so your operators can get down to their job sooner.

Decide a Target Time to Answer Calls
You should know what is possible in a matter of a few weeks. Do not attempt to go too tight on this one. It is better to build in say 10% slack that you can always trim in future. Once you have decided this, you can implement your Kanban system.

Introducing Kanban in Your Call Centre Operation
Monitor your rate of incoming calls through your contact centre, and adjust your operator-demand metric on an ongoing basis. Use this to calculate your over / under demand factor. Every operator should know the value on this Kanban ticket. It will tell them whether to speed up a little, or slow down a bit so they deliver the effort the call rate demands. It will also advise the supervisor when to call up reserves.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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Quality Assurance

 

There is a truism that goes “The bitterness of poor quality is remembered long after the sweetness of low price has faded from memory”.

While every consumer can probably relate to this idea, business enterprises offering goods and services are the ones that should heed this the most.

Quality Management Systems

The concept of quality was first introduced in the 1800’s. Goods were then still mass-produced, created by the same set of people, with a few individuals assigned to do some “tweaking” on the product to bring it to acceptable levels. Their idea of quality at that time may not have been that well-defined, but it marked the beginnings of product quality and customer satisfaction as we know it now.

Since then, quality has developed into a very basic business principle that every organisation should strive to achieve. Yet while every business recognises the importance of offering product and service quality, it is not something that can be achieved overnight.

If you’ve been in any type of business long enough, you should know that there is no “quick-fix” to achieving quality. Instead, it is an evolving process that needs to be continually worked on. And this is where the importance of having a workable Quality Management System (QMS) in an organisation comes in.

Whatever Quality tools and processes you need to implement the change needed in your organisation, we can help you with it. We are ready to work in partnership with your team to develop strategic systems which will produce significant performance improvements geared towards the achievement of quality.

What is a Quality Management System?

A Quality Management System is defined as the set of inter-related objectives, processes, and operating procedures that organisations use as a guide to help them implement quality policies and attain quality objectives.

Needless to say, the ultimate goal of every quality management system is to establish quality as a core value of the company among all employees, and across all products and services. Why? Because quality services make for happy customers, and satisfied customers ensure continued business for the company.

A Quality Management System does not stop with simply having a set of guidelines that the leaders of a company can easily have their organisation members accept and adhere to. Rather, effective QMS can be implemented when management provides a culture of pride and patience, which will inspire acceptance of individual and group responsibility.

In this manner, not only the heads of the organisation but the employees as well, will develop the desire to achieve company goals that will benefit:

  • All contributing teams;
  • The customers; and
  • The company as a whole.

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