A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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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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Without Desktop Virtualisation, you can’t attain True Business Continuity

Even if you’ve invested on virtualisation, off-site backup, redundancy, data replication, and other related technologies, I?m willing to bet your BC/DR program still lacks an important ingredient. I bet you’ve forgotten about your end users and their desktops.

Picture this. A major disaster strikes your city and brings your entire main site down. No problem. You’ve got all your data backed up on another site. You just need to connect to it and voila! you’ll be back up and running in no time.

Really?

Do you have PCs ready for your employees to use? Do those machines already have the necessary applications for working on your data? If you still have to install them, then that’s going to take a lot of precious time. When your users get a hold of those machines, will they be facing exactly the same interface that they’ve been used to?

If not, more time will be wasted as they try to familiarise themselves. By the time you’re able to declare ?business as usual?, you’ll have lost customer confidence (or even customers themselves), missed business opportunities, and dropped potential earnings.

That’s not going to happen with desktop virtualisation.

The beauty of?virtualisation

Virtualisation in general is a vital component in modern Business Continuity/Disaster Recovery strategies. For instance, by creating multiple copies of virtualised disks and implementing disk redundancy, your operations can continue even if a disk breaks down. Better yet, if you put copies on separate physical servers, then you can likewise continue even if a physical server breaks down.

You can take an even greater step by placing copies of those disks on an entirely separate geographical location so that if a disaster brings your entire main site down, you can still gain access to your data from the other site.

Because you’re essentially just dealing with files and not physical hardware, virtualisation makes the implementation of redundancy less costly, less tedious, greener, and more effective.

But virtualisation, when used for BC/DR, is mostly focused on the server side. As we’ve pointed out earlier in the article, server side BC/DR efforts are not enough. A significant share of business operations are also dependent on the client side.

Desktop virtualisation (DV) is very similar to server virtualisation. It comes with nearly the same kind of benefits too. That means, a virtualised desktop can be copied just like ordinary files. If you have a copy of a desktop, then you can easily use that if the active copy is destroyed.

In fact, if the PC on which the desktop is running becomes incapacitated, you can simply move to another machine, stream or install a copy of the virtualised desktop there, and get back into the action right away. If all your PCs are incapacitated after a disaster, rapid provisioning of your desktops will keep customers and stakeholders from waiting.

In addition to that, DV will enable your user interface to look like the one you had on your previous PC. This particular feature is actually very important to end users. You see, users normally have their own way of organising things on their desktops. The moment you put them in front of a desktop not their own, even if it has the same OS and the same set of applications, they?ll feel disoriented and won’t be able to perform optimally.

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The Connection Between Six Sigma and CRM

Six Sigma is an industrial business strategy directed at improving the quality of process outputs by eliminating errors and system variables. The end objective is to achieve a state where 99.99966% of events are likely to be defect free. This would yield a statistical rating of Sigma 6 hence the name.

The process itself is thankfully more user-friendly. It presents a model for evaluating and improving customer relationships based on data provided by an automated customer relations management (CRM) system. However in the nature of human interaction we doubt the 99.99966% is practically achievable.

Six Sigma Fundamentals

The basic tenets of the business doctrine and the features that set off are generally accepted to be the following:

  1. Continuous improvement is essential for success
  1. Business processes can be measured and improved
  1. Top down commitment is fundamental to sustained improvement
  1. Claims of progress must be quantifiable and yield financial benefits
  1. Management must lead with enthusiasm and passion
  1. Verifiable data is a non-negotiable (no guessing)

Steps Towards the Goal

The five basic steps in Six Sigma are define the system, measure key aspects, analyse the relevant data, improve the method, and control the process to sustain improvements. There are a number of variations to this DMAIC model, however it serves the purpose of this article. To create a bridge across to customer relationships management let us assume our CRM data has thrown out a report that average service times in our fast food chicken outlets are as follows.

<2 Minutes 3 to 8 Minutes 9 to 10 Minutes >10 Minutes
45% 30% 20% 5%
Table: Servicing Tickets in Chippy?s Chicken Caf?s

Using DMAIC to unravel the reasons behind this might proceed as follows

  • Define the system in order to understand the process. How are customers prioritised up front, and does the back of store follow suit?
  • Break the system up into manageable process chunks. How long should each take on average? Where are bottlenecks most likely to occur?
  • Analyse the ticket servicing data by store, by time of day, by time of week and by season. Does the type of food ordered have a bearing?
  • Examine all these variables carefully. Should there for example be separate queues for fast and slower orders, are there some recipes needing rejigging
  • Set a goal of 90% of tickets serviced within 8 minutes. Monitor progress carefully. Relate this to individual store profitability. Provide recognition.

Conclusion

A symbiotic relation between CRM and a process improvement system can provide a powerful vehicle for evidencing customer care and providing feedback through measurable results. Denizon has contributed to many strategically important systems.?

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