How Bouygues manages an Empire-Sized Footprint

Bouygues is into telecoms / media, and building and road construction. It also knows it has to watch its energy footprint closely. Owning 47% of energy giant Alstom keeps it constantly in the media spotlight. Shall we find out more about its facility management policies?

The journal Premises and Facilities Management interviewed MD Martin Bouygues on his personal opinions concerning managing energy consumption in facilities. He began by commenting that this was hardly a subject for the C-Suite in years gone by. Low-level clerks simply paid the bills following which the actual amounts were lost in the general expenses account. That of course has changed.

Early pressure came from soaring energy bills, which were pursued by a whole host of electricity-saving gadgets. However, it was only after the carbon crisis caught business by surprise that the link was forged to aerial pollution, and the social responsibilities of big business to help with the solution. The duty to have an energy strategy became an obligation eagerly policed by organisations such as Greenpeace.

Unsurprisingly, Martin Bouygues? advice begins with keeping energy consumption and its carbon footprint as high up on the agenda as health and safety. ?It needs bravery and a lot of hard work to get it there,? he says, ?so perseverance is the key?. 

The company has developed proprietary software that enables it to pull data from remote sensors in more than 80 countries every fifteen minutes. A single large building can contribute 50 million data items annually making data big business in the system. Every building has an allocated energy performance contract against which results are reported monthly, as a basis for reviewing progress.

The system is intelligent and able to incorporate low-occupancy periods such as weekends and public holidays. What is measured gets managed. We all know that, but how many of us apply the principle to our energy bills. With assistance from ecoVaro, the possible becomes real.

We offer a similar service to the Bouygues model with one notable exception. You don’t buy the software and you only pay when you use it. Our systems are simply designed for busy financial managers.

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Are Master Data Management and Hadoop a Good Match?

Master Data is the critical electronic information about the company we cannot afford to lose. Accordingly, we should sanitise it, look after it, and store it safely in several separate places that are independent of each other. The advent of Big Data introduced the current era of huge repositories ?in the clouds?. They are not, of course but at least they are remote. This short article includes a discussion about Hadoop, and whether this is a good platform to back up your Master Data.

About Hadoop

Hadoop is an open-source Apache software framework built on the assumption that hardware failure is so common that backups are unavoidable. It comprises a storage area and a management part that distributes the data to smaller nodes where it processes faster and more efficiently. Prominent users include Yahoo! and Facebook. In fact more than half Fortune 50 companies were using Hadoop in 2013.

Hadoop – initially launched in December 2011 ? has survived its baptism of fire and became a respected, reliable option. But is this something the average business owner can tackle on their own? Bear in mind that open source software generally comes with little implementation support from the vendor.

The Hadoop Strong Suite

  • Free to download, use and contribute to
  • Everything you need ?in the box? to get started
  • Distributed across multiple fire-walled computers
  • Fast processing of data held in efficient cluster nodes
  • Massive scaleable storage you are unlikely to run out of

Practical Constraints

There is more to Hadoop than writing to WordPress. The most straightforward solutions are uploading using Java commands, obtaining an interface mechanism, or using third party vendor connectors such as ACCESS or SAS. The system does not replace the need for IT support, although it is cheap and exceptionally powerful.

The Not-Free Safer Option

Smaller companies without in-depth in-house support are wise to engage with a technical intermediary. There are companies providing commercial implementations followed by support. Microsoft, Amazon and Google among others all have commercial versions in their catalogues, and support teams at the end of the line.

What Sub-Metering did for Nissan in Tennessee

When Nissan built its motor manufacturing plant in Smyrna 30 years ago, the 5.9 million square-foot factory employing over 8,000 people was state of art. After the 2005 hurricane season sky-rocketed energy prices, the energy team looked beyond efficient lighting at the more important aspect of utility usage in the plant itself. Let’s examine how they went about sub-metering and what it gained for them.

The Nissan energy team faced three challenges as they began their study. They had a rudimentary high-level data collection system (NEMAC) that was so primitive they had to transfer the data to spread-sheets to analyse it. To compound this, the engineering staff were focused on the priority of getting cars faster through the line. Finally, they faced the daunting task of making modifications to reticulation systems without affecting manufacturing throughput. But where to start?

The energy team chose the route of collaboration with assembly and maintenance people as they began the initial phase of tracking down existing meters and detecting gaps. They installed most additional equipment during normal service outages. Exceptions were treated as minor jobs to be done when convenient. Their next step was to connect the additional meters to their ageing NEMAC, and learn how to use it properly for the first time.

Although this was a cranky solution, it had the advantage of not calling for additional funding which would have caused delays. However operations personnel were concerned that energy-saving shutdowns between shifts and over weekends could cause false starts. ?We’ve already squeezed the lemon dry,? they seemed to say. ?What makes you think there?s more to come??

The energy team had a lucky break when they stumbled into an opportunity to prove their point early into implementation. They spotted a four-hourly power consumption spike they knew was worth examining. They traced this to an air dryer that was set to cyclical operation because it lacked a dew-point sensor. The company recovered the $1,500 this cost to fix, in an amazing 6 weeks.

Suitably encouraged and now supported by the operating and maintenance departments, the Smyrna energy team expanded their project to empower operating staff to adjust production schedules to optimise energy use, and maintenance staff to detect machines that were running without output value. The ongoing savings are significant and levels of shop floor staff motivation are higher.

Let’s leave the final word to the energy team facilitator who says, ?The only disadvantage of sub-metering is that now we can’t imagine doing without it.?

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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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