Is Your Project Agile, a Scrum or a Kanban?

Few projects pan out the way we expect when starting out. This is normal in any creative planning phase. We half suspect the ones that follow a straight line are the exceptions to the rule. Urban legend has it; Edison made a thousand prototypes before his first bulb lit up, and then went on to comment, ?genius is 1% inspiration, 99% perspiration?. Later, he added that many of life’s failures are people who did not realise just how close they were to success when they gave up.

So be it to this day, and so be it with project planning too. There is no one size fits all approach when it comes to it. Agile, Scrum and Kanban each have their supporters and places where they do well. Project planning often works best when we use a sequential combination of them, appropriate to what is currently happening on the ground.

Of the three, Agile is by far the most comprehensive. It provides a structure that begins with project vision / conceptualisation, and goes as far as celebration when the job is over, and retrospective discussion afterwards. However, the emphasis on daily planning meetings may dent freethinking, and even smother it.

Scrum on the other hand says ?forget all that bureaucracy?. There is a job to do and today is the day we are going to do it. Although the core Agile teamwork is still there it ignores macro project planning, and could not be bothered with staying in touch with customers. If using Scrum, it is best to give those jobs to someone else.

The joker in the pack is Kanban, It believes that rules are there to substitute for thought, and that true progress only comes from responsible freedom. It belongs in mature organisations that have passed through Scrum and Agile phases and have embarked on a voyage towards perfection.

That said, there can be no substitute for human leadership, especially when defined as the social influence that binds the efforts of others towards a single task.

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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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A Definitive List of the Business Benefits of Cloud Computing ? Part 3

Strengthens business continuity/disaster recovery capabilities

Today’s business landscape calls for companies to have reliable business continuity and disaster recovery capabilities. After all, when the system goes down, customers and even employees would rarely ask ‘why‘ or ‘what happened‘ but instead go directly to the ‘how soon can we get back up‘ part.

So unless they’ve been struck by the same unforeseen disaster your business is also experiencing, a couple of hours downtime is plenty enough for most of these people. What’s worse is when they simply don’t wait until they get access again and just go to other providers that can offer the same services. In short, your inability to provide continuous IT and business services could translate to lost opportunities which your competition would only be too willing to gain. And that’s not even counting the possibility of losing essential data and other potential negative impact that critical IT failure can bring about.

The answer to avoiding such a scenario is of course, having a sound business continuity and disaster recovery plan in place. But this is actually easier said than done.

Traditionally, setting up a business continuity plan entailed some tedious procedures in addition to very costly infrastructure. We’re talking here about acquiring and maintaining practically a replication of the hardware infrastructure and environments currently existing for business-critical systems and data. Note that these mirror systems should be set-up, housed, and maintained in a remote facility or location.

Making the deployment even more complex is the constant need to update the data in storage as well as keep software applications in sync between the system in use and the one on standby mode. This process would involve the physical transfer of data and syncing of applications, which is cumbersome and again, expensive.

While large enterprises would not even think twice about having to spend so much to ensure that operations would never come to a grinding halt, most small and mid-sized organisations would not have the required financial means for them to even start considering this option. Often, the bulk of their disaster recovery plan would simply consist of some tape backups, and a lot of hoping that they would never have to suffer from any outage or IT failure.

But all that can be changed with the arrival of cloud computing.

A cloud strategy offers an affordable solution for business continuity and disaster recovery for SMBs with limited resources and even big companies trying to minimise expenses by looking for alternative options.

A reliable service provider would already have the required infrastructure and software vital to a viable BC/DR plan and complete with the appropriate security measures. Organisations need not spend upfront for these facilities, but get to benefit from having updated data backup and a virtualised mirror system that would allow them to quickly get back up in the event of an outage or catastrophic disaster.

When looking to the cloud for a cost-effective BC/DR plan however, it’s worth keeping in mind that not all cloud providers are created equal. That’s why businesses also have many important factors to take into account before signing cloud contracts.

Yes, provision for continuity and and taking necessary precautions against outages are inherent in the cloud service itself, but you’d be surprised how many of these providers don’t actually take responsibility for service interruption. To give organisations some assurance of the cloud company’s capacity for continued service, contracts should stipulate availability guarantees and liability for downtime that the provider is willing to answer for.

Once these relevant issues are ironed out however, it’s easy for business to see how cloud-based data storage and computing can significantly lower the costs involved for SMB BC/DR while greatly improving efficiency, mobility, and collaboration capabilities.

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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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