How Alcoa Canned the Cost of Recycling

Alcoa is one of the world?s largest aluminium smelting and casting multinationals, and involves itself in everything from tin cans, to jet engines to single-forged hulls for combat vehicles. Energy costs represent 26% of the company?s total refining costs, while electricity contributes 27% of primary production outlays. Its Barberton Ohio plant shaved 30% off both energy use and energy cost, after a capital outlay of just $21 million, which for it, is a drop in the bucket.

Aluminium smelting is so expensive that some critics describe the product as ?solid electricity?. In simple terms, the method used is electrolysis whereby current passes through the raw material in order to decompose it into its component chemicals. The cryolite electrolyte heats up to 1,000 degrees C (1,832 degrees F) and converts the aluminium ions into molten metal. This sinks to the bottom of the vat and is collected through a drain. Then they cast it into crude billets plugs, which when cooled can be re-smelted and turned into useful products.

The Alcoa Barberton factory manufactures cast aluminium wheels across approximately 50,000 square feet (4,645 square meters) of plant. It had been sending its scrap to a sister company 800 miles away; who processed it into aluminium billets – before sending them back for Barberton to turn into even more wheels. By building its own recycling plant 60 miles away that was 30% more efficient, the plant halved its energy costs: 50% of this was through process engineering, while the balance came from transportation.

The transport saving followed naturally. The recycling savings came from a state-of-the-art plant that slashed energy costs and reduced greenhouse gas emissions. Interestingly enough, processing recycled aluminium uses just 5% of energy needed to process virgin bauxite ore. Finally, aluminium wheels are 45% lighter than steel, resulting in an energy saving for Alcoa Barberton?s customers too.

The changes helped raise employee awareness of the need to innovate in smaller things too, like scheduling production to increase energy efficiency and making sure to gather every ounce of scrap. The strategic change created 30 new positions and helped secure 350 existing jobs.

The direction that Barberton took in terms of scrap metal recycling was as simple as it was effective. The decision process was equally straightforward. First, measure your energy consumption at each part of the process, then define the alternatives, forecast the benefits, confirm and implement. Of course, you also need to be able to visualise what becomes possible when you break with tradition.

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Spreadsheet Risks in Banks

No other industry perhaps handles such large volumes of critical financial data more than the banking industry. For decades now, spreadsheets have become permanent fixtures in the front-line reporting tool sets of banks, providing organised information when and where needed.

But as banks enter into a period of heightened credit risks, elevated levels of fraud, and greater regulatory scrutiny, many are wondering if continued reliance on spreadsheets is a wise decision for banks today.

The downfall of Lehman Brothers which eventually led to its filing for Chapter 11 bankruptcy protection on September 15, 2008, served as a wake up call for many institutions across the globe to make a serious examination of their own risk management practices. But would these reforms include evaluating the security of user developed applications (UDAs), the most common of which are spreadsheets, and putting specific guidelines as to when they can – or cannot be – used?

Banks and Spreadsheet Use

Banks have been known to utilise spreadsheets systems for many critical functions because most personnel are well-acquainted with them, and the freedom of being able to develop customised reports without needing to consult with the IT department offers flexibility and convenience. In fact, more than having a way to do financial budgeting and analysing customer profitability, even loan officers and trade managers have become reliant on spreadsheets for risk management reporting and for making underwriting decisions.

But there are more than a few drawbacks to using spreadsheets for these tasks, and the sooner bank executives realise these, the sooner they can adopt better solutions.

General Limitations

Spreadsheets are far from being data base systems and yet more often than not, they are expected to act as such, with figures constantly added and formulas edited to produce the presumably right set of reports.

In addition, data integrity is always a cause for concern as most values in spreadsheets are entered as manual inputs. Even the mere misplacement of a comma or a negative sign, or an inadvertent ?edit? to a formula can also be a source of significant changes in the outcome.

Confidentiality risk is also another drawback of the use of spreadsheets in banks as these tools do not have adequate?access controls to limit access to only authorised individuals. Pertinent financial information that fall into the wrong hands can lead to a whole new set of problems including the possibility of fraud.

Risks in Trading

For trading transactions, spreadsheets can prove to be of immense use – but only for small market volumes. As trade volumes increase and the types vary, spreadsheets are no longer a viable solution and may likely become more of a hindrance, with calculations taking longer in the face of bigger transaction amounts and growing transaction data.

And in trading, there is always the need for rigorous computational functions. Computing for the Value at Risk (VaR) for large portfolios for instance, is simply way beyond the capabilities of spreadsheets. Banks that persist in using them are increasing the risk of loss on those portfolios. Or, they can be opening up?opportunities for fraud?as Allied Irish Bank (in the case of John Rusnak – $690 million) learned the hard way.

Risks in Underwriting

Bankers who use spreadsheets as their main source of information for underwriting procedures also face certain limitations. Loan transactions require that borrowers? financial data be centralised and easily accessible to risk officers and lending officers involved in making decisions. With spreadsheets, there is no simple and secure way of doing that. Information can be pulled from different sources – individual tax returns, corporate tax documents, partnership documents, audited financial statements – hence there is difficulty in verifying that these reports adhere to underwriting policies.

Spreadsheet control and monitoring

Financial institutions which are having difficulty weaning themselves from the convenience and simplicity that spreadsheets offer are looking for possible control solutions. Essentially, they want to find ways that allow them to continue using these UDAs and yet somehow eliminate the?spreadsheet risks?and limitations involved.

Still, the debate goes back and forth on whether adequate control measures can be implemented on spreadsheets so that that the risks are mitigated. Many services have come forward to herald innovative solutions for better spreadsheet management. But at the end of the day, there really is no guarantee that such solutions would suffice.

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Spreadsheet Risks in Banks


Top 10 Disadvantages of Spreadsheets


Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry


How Internal Auditors can win the War against Spreadsheet Fraud


Spreadsheet Reporting – No Room in your company in an age of Business Intelligence


Still looking for a Way to Consolidate Excel Spreadsheets?


Disadvantages of Spreadsheets


Spreadsheet woes – ill equipped for an Agile Business Environment


Spreadsheet Fraud


Spreadsheet Woes – Limited features for easy adoption of a control framework


Spreadsheet woes – Burden in SOX Compliance and other Regulations


Spreadsheet Risk Issues


Server Application Solutions – Don’t let Spreadsheets hold your Business back


Why Spreadsheets can send the pillars of Solvency II crashing down

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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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Article 8 of the EU Energy Efficiency Directive ? Orientation

Following in-depth discussion of the UK?s ESOS response, we decided to backtrack to the source, especially since every EU member is facing similar challenges. The core purpose of the directive is to place a pair of obligations on member states. These are

  1. To promote the availability of energy audits among final customers in all sectors, and;
  2. To ensure that enterprises that are not SMEs carry out energy audits at least every four years.

Given the ability for business to look twice at every piece of legislation it considers unproductive, the Brussels legislators took care to define what constitutes an enterprise larger than an SME.

Definition of a Large Undertaking

A large undertaking meets one or both of the following conditions:

  1. It employs 250 or more people
  2. Its annual turnover is more than ?50 million and its balance sheet total exceeds ?43 million

Rules for Energy Audits

If accredited / qualified in-house specialists are unavailable then independent experts should supervise audits. The talent shortage seems common to many EU businesses. In hindsight, the Union could have ramped up slower, especially since the first compliance date of 5 December 2015 does not leave much swing room.

ecoVaro doubts there was a viable alternative, given the urgent imperative to beat back the scourge of carbon that is threatening the viability of our planet. The legislators must have been of a similar mind when laying down the guidelines. Witness for example the requirement that penalties be ?effective, proportionate and dissuasive?.

In order to be compliant, an energy audit must

  1. Be based on twelve months of verifiable data that is
    • over a continuous period beginning no more than 24 months before the beginning of the energy audit, and;
    • identifies energy saving opportunities including paths to their achievement
  2. Analyse the participant’s energy consumption and energy efficiency
  3. Have not been used as the basis for an energy audit in a previous compliance period

Measurement of current status and progress tracing are at the core of energy saving and good governance generally. EcoVaro has a powerhouse of software tools available on the cloud to help project teams save time and money.

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