Still Looking For A Way To Consolidate Excel Spreadsheets?

We use Excel spreadsheets everyday. We use them to prepare budgets and reports. We even use them when drafting plans and forecasts. With this ubiquitous office application, entering data and carrying out on-the-spot computations and analysis is quick and easy. However, when it’s time to consolidate Excel data, I won’t be surprised if you wished there was an easy way.

In fact, you were probably looking for a solution before landing on this page, right?

Because budgeting, reporting, planning, and forecasting are normally done by a group of people and not just by one individual, spreadsheets bearing the necessary data can be scattered in different folders, desktops, offices, and, in the case of really large organisations, geographical locations.

How are these data brought together? Through email attachments or by sharing folders in a local area network. Each member of the working team sends out copies of their own spreadsheets to other members, who then review them, make necessary changes, then send back to the source. The files can go back and forth until everyone is satisfied.

With each sending, sharing, and edit, business critical data gets exposed to all sorts of spreadsheet risks. Copy-paste errors, omission of a negative sign, erroneous inputs, accidental deletions, and even fraudulent manipulations can take place. And because each member can end up with multiple versions of a single spreadsheet, the chance of working on the wrong version exists.

So when all the data gets consolidated and finalised, it is possible for the end product to contain significant errors. It may not happen all the time, but it certainly can happen.

But that’s not the only disadvantage of spreadsheets. The entire process of comparing cells and sheets, copy-pasting data, linking cells, writing formulas, and specifying ranges can be very tedious, not to mention time-consuming. With spreadsheets, beating deadlines is always an almost impossible exercise.

What you need is a solution that will no longer require you to consolidate Excel spreadsheets. One that is faster, more reliable, and significantly less error-prone. Denizon has a server-based solution that has all those capabilities and much more.

With a server-based solution, all your data is stored in one place. Everyone is working on the same data source, so consolidation is fast and easy. Everyone becomes synchronised and no one has to worry about working on the wrong version.

Read more about our server-based solution

 

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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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FUJIFILM Cracks the Energy Code

FUJIFILM was in trouble at its Dayton, Tennessee plant in 2008 where it produced a variety of speciality chemicals for industrial use. Compressed-air breakdowns were having knock-on effects. The company decided it was time to measure what was happening and solve the problem. It hoped to improve reliability, cut down maintenance, and eliminate relying on nitrogen for back-up (unless the materials were flammable).

The company tentatively identified three root causes. These were (a) insufficient system knowledge within maintenance, (b) weak spare part supply chain, and (c) generic imbalances including overstated demand and underutilised supply. The maintenance manager asked the U.S. Department of Energy to assist with a comprehensive audit of the compressed air system.

The team began on the demand side by attaching flow meters to each of several compressors for five days. They noticed that – while the equipment was set to deliver 120 psi actual delivery was 75% of this or less. They found that demand was cyclical depending on the production phase. Most importantly, they determined that only one compressor would be necessary once they eliminated the leaks in the system and upgraded short-term storage capacity.

The project team formulated a three-stage plan. Their first step would be to increase storage capacity to accommodate peak demand; the second would be to fix the leaks, and the third to source a larger compressor and associated gear from a sister plant the parent company was phasing out. Viewed overall, this provided four specific goals.

  • Improve reliability with greater redundancy
  • Bring down system maintenance costs
  • Cut down plant energy consumption
  • Eliminate nitrogen as a fall-back resource

They reconfigured the equipment in terms of lowest practical maintenance cost, and moved the redundant compressors to stations where they could easily couple as back-ups. Then they implemented an online leak detection and repair program. Finally, they set the replacement compressor to 98 psi, after they determined this delivered the optimum balance between productivity and operating cost.

Since 2008, FUJIFILM has saved 1.2 million kilowatt hours of energy while virtually eliminating compressor system breakdowns. The single compressor is operating at relatively low pressure with attendant benefits to other equipment. It is worth noting that the key to the door was measuring compressed air flow at various points in the system.

ecoVaro specialises in analysing data like this on any energy type.?

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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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