Monitoring Water Banks with Telemetrics

Longstanding droughts across South Australia are forcing farmers to rethink the moisture in the soil they once regarded as their inalienable right. Trend monitoring is an essential input to applying pesticides and fertilisers in balanced ratios. Soil moisture sensors are transmitting data to central points for onward processing on a cloud, and this is making a positive difference to agricultural output.

Peter Buss, co-founder of Sentek Technology calls ground moisture a water bank and manufactures ground sensors to interrogate it. His hometown of Adelaide is in one of the driest states in Australia. This makes monitoring soil water even more critical, if agriculture is to continue. Sentek has been helping farmers deliver optimum amounts of water since 1992.

The analogy of a water bank is interesting. Agriculturists must ?bank? water for less-than-rainy days instead of squeezing the last drop. They need a stream of online data and a safe place somewhere in the cloud to curate it. Sentek is in the lead in places as remote as Peru?s Atacamba desert and the mountains of Mongolia, where it supports sustainable floriculture, forestry, horticulture, pastures, row crops and viticulture through precise delivery of scarce water.

This relies on precision measurement using a variety of drill and drop probes with sensors fixed at 4? / 10cm increments along multiples of 12? / 30cm up to 4 times. These probe soil moisture, soil temperature and soil salinity, and are readily re-positioned to other locations as crops rotate.

Peter Buss is convinced that measurement is a means to the end and only the beginning. ?Too often, growers start watering when plants don’t really need it, wasting water, energy, and labour. By monitoring that need accurately, that water can be saved until later when the plant really needs it.? He goes on to add that the crop is the ultimate sensor, and that ?we should ask the plant what it needs?.

This takes the debate a stage further. Water wise farmers should plant water-wise crops, not try to close the stable door after the horse has bolted and dry years return. The South Australia government thinks the answer also lies in correct farm dam management. It wants farmers to build ones that allow sufficient water to bypass in order to sustain the natural environment too.

There is more to water management than squeezing the last drop. Soil moisture goes beyond measuring for profit. It is about farming sustainably using data from sensors to guide us. ecoVaro is ahead of the curve as we explore imaginative ways to exploit the data these provide for the common good of all.

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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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Symbion Pharmacy Services? Definition of Responsibility

A ?symbion? is an organism in a symbiotic (i.e. mutually beneficial) relationship with another one. In the case of Australia?s giant Symbion Pharmacy Services, this means supplying and delivering over-counter Chemmart medicines to more than 3,000 hospital and retail pharmacies, while remaining mindful of its carbon footprint.

In 1999, the company with the tagline ?life matters? and a desire to be seen as ?a good corporate citizen? decided it was time to measure exactly what it was pumping out from 12 facilities and over 200 vehicles. This was a voluntary decision as even now there is still no carbon emissions law in Australia (although no doubt being a ?first mover? will put the company in a competitive position when this inevitably comes).

Symbion decided to install emission detection devices and connect these to a central monitoring system with the intention of managing what these measured. There were two stages to this process. First, Symbion determined its reporting requirements based on one of its larger warehouses. Following that, it established a carbon footprint for each of its wholly owned and managed facilities. This put it in a position to:

  • Analyse total emissions down to a level of detail where it understood the contribution of each source
  • Use big data management tools to identify carbon hotspots for priority remedial action
  • Inform the affected workforce, explain the monitoring system and keep them in the loop
  • Separately manage energy abatement programs such as lighting and delivery routes

The program also had productivity spin-offs in that it focused management attention on the processes behind the emissions that were ripe for material and system improvements. It also provided marketing leverage. Symbion?s customers are in the wellness business, ahead of the curve when it comes to how emissions contribute to chronic illness, and aware of the cost of this in terms of human capital.

EcoVaro could help you manage your throughputs by analysing your data on our cloud-based system. This includes trending your metrics, comparing them to your industry seasonal average, and providing you with a business-like view of how well you are doing.

Our service reduces your reliance on (and the cost of) third party audits, and simplifies the reporting process to your controlling authority. It simply makes more sense to contract your software out this way, and only pay for it when you need it.

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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