What Heijunka is & How it Smooths Call Centre Production

The Japanese word Heijunka, pronounced hi-JUNE-kuh means ?levelling? in the sense of balancing workflows. It helps lean organizations shift priorities in the face of fluctuating customer demand. The goal is to have the entire operation working at the same pace throughout, by continuously adjusting the balance between predictability, flexibility, and stability to level out demand.

Henry Ford turned the American motor manufacturing industry upside down by mass-producing his iconic black motor cars on two separate production lines. In this photograph, body shells manufactured upstairs come down a ramp and drop onto a procession of cars almost ready to roll in 1913.

Smoothing Production in the Call Centre Industry

Call Centres work best in small teams, each with a supervisor to take over complex conversations. In the past, these tended to operate in silos with each group in semi-isolation representing a different set of clients. Calls came through to operators the instant the previous ones concluded. By the law of averages, inevitably one had more workload than the rest at a particular point in time as per this example.

Modern telecoms technology makes it possible to switch incoming lines to different call centre teams, provided these are multi-skilled. A central operator controls this manually by observing imbalanced workflows on a visual system called a Heijunka Box. The following example comes from a different industry, and highlights how eight teams share uneven demand for six products.

This departure from building handmade automobiles allowed Henry to move his workforce around to eliminate bottlenecks. For example, if rolls of seat leather arrived late he could send extra hands upstairs to speed up the work there, while simultaneously slowing chassis production. Ford had the further advantage of a virtual monopoly in the affordable car market. He made his cars at the rate that suited him best, with waiting lists extending for months.

A Modern, More Flexible Approach

Forces of open competition and the Six Sigma drive for as-close-to-zero defects dictates a more flexible approach, as embodied in this image published by the Six Sigma organisation. This represents an ideal state. In reality, one force usually has greater influence, for example decreasing stability enforces a more flexible approach.

Years ago, Japanese car manufacturer Toyota moved away from batching in favour of a more customer-centric approach, whereby buyers could customise orders from options held in stock for different variations of the same basic model. The most effective approach lies somewhere between Henry Ford?s inflexibility and Toyota?s openness, subject to the circumstances at the moment.

A Worked Factory Example

The following diagram suggests a practical Heijunka application in a factory producing three colours of identical hats. There are two machines for each option, one or both of which may be running. In the event of a large order for say blue hats, the company has the option of shifting some blue raw material to the red and green lines so to have the entire operation working at a similar rate.

Predictability, Flexibility, and Stability at Call Centre Service

The rate of incoming calls is a moving average characterised by spikes in demand. Since the caller has no knowledge whether high activity advisories are genuine, it is important to service them as quickly as possible. Lean process engineering provides technology to facilitate flexibility. Depending on individual circumstances, each call centre may have its own definition of what constitutes an acceptably stable situation.

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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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Why DevOps Matters: Things You Need to Know

DevOps creates an agile relationship between system development and operating departments, so the two collaborate in providing results that are technically effective, and work well for customers and users. This is an improvement over the traditional model where development delivers a complete design ? and then spends weeks and even months afterwards, fixing client side problems that should never have occurred.
Writing for Tech Radar Nigel Wilson explains why it is important to roll out innovation quickly to leverage advantage. This implies the need for a flexible organisation capable of thinking on its feet and forming matrix-based project teams to ensure that development is reliable and cost effective.
Skirmishes in Boardrooms
This cooperative approach runs counter to traditional silo thinking, where Operations does not understand Development, while Development treats the former as problem children. This is a natural outcome of team-centred psychology. It is also the reason why different functions pull up drawbridges at the entrance to their silos. This situation needs managing before it corrodes organization effectiveness. DevOps aims to cut through this spider web of conflict and produce faster results.

The Seeds of Collaboration

Social and personal relationships work best when the strengths of each party compensate the deficiencies of the other. In the case of development and operations, development lacks full understanding of the daily practicalities operating staff face. Conversely, operations lacks ? and should lack knowledge of the nuances of digital automation, for the very reason it is not their business.
DevOps straddles the gap between these silos by building bridges towards a co-operative way of thinking, in which matrix-teams work together to define a problem, translate it into needs and spec the system to resolve these. It is more a culture than a method. Behavioural change naturally leads to contiguous delivery and ongoing deployment. Needless to say only the very best need apply for the roles of client representative, functional tester and developer lead.

Is DevOps Worth the Pain of Change?

Breaking down silos encroaches on individual managers? turf. We should only automate to improve quality and save money. These savings often distil into organisational change. The matrix team may find itself in the middle of a catfight. Despite the pain associated with change resistance, DevOps more than pays its way in terms of benefits gained. We close by considering what these advantages are.

An Agile Matrix Structure ? Technical innovation is happening at a blistering rate. The IT industry can no longer afford to churn out inferior designs that take longer to fix than to create. We cannot afford to allow office politics to stand in the way of progress. Silos and team builds are custodians of routine and that does not sit well with development.

An Integrated Organization ? DevOps not only delivers operational systems faster through contiguous testing. It also creates an environment whereby cross-border teams work together towards achieving a shared objective. When development understands the challenges that operations faces ? and operations understands the technical limiters – a new perspective emerges of ?we are in this together?.

The Final Word ? With understanding of human dynamics pocketed, a DevOps project may be easier to commission than you first think. The traditional way of doing development – and the waterfall delivery at the end is akin to a two-phase production line, in which liaison is the weakest link and loss of quality inevitable.

DevOps avoids this risk by having parties work side-by-side. We need them both to produce the desired results. This is least until robotics takes over and there is no longer a human element in play.

Saving Energy Step 1 ? Implementing a Management System

There has been much hype down the years regarding whether management is art or science. Thankfully, where people are concerned the pendulum has swung away from standard times in sweatshops in the west. However, when it comes to measuring physical things like harvest per square meter and the amount of energy consumed there is no substitute for scientific measurement, and this implies a system.

Managing energy cost and consumption down is like any other strategy. American engineer / statistician / management consultant W. Edwards Demming may have passed on in 1993. However he was as right as ever when he said:

  1. When people and organizations focus primarily on quality, this tends to increase and costs fall over time.
  1. However, when people and organizations focus primarily on costs, costs tend to rise and quality declines over time.

Demming believed that 90% of organizational problems arise from systems we put in place ourselves. This can be because we are so accustomed to them that we fail to notice when they are no longer relevant. The currently prevailing laissez faire towards energy is a case in point. What is managed improves and what is not, deteriorates. We know this. Let us take a look at how to apply this principle to energy management.

First, you need to get the subject out the closet and talk about it. How often do you do this is your boardroom, and how does energy rank against other priorities? Good governance is about taking up a position and following through on it. Here is a handy checklist you may like to use.

  • Do we use a consistent language when we talk about energy? Is it electricity, or carbon emitted (or are we merely fretting over cost).
  • How well engaged are we as a company? Looking up and down and across the organization are there points where responsibility stops.
  • How well have we defined accountability? Do we agree on key performance areas and how to report on them.
  • Are we measuring energy use at each point of the business? When did we last challenge the assumption that ?we’re doing okay?.
  • Have we articulated our belief that quality is endless improvement, or are we simply chasing targets because someone says we should.

A management system is a program of policies, processes and methods to ensure achievement of goals. The next blog focuses on tools and techniques that support this effort.

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