Saving Energy Step 2 ? More Practical Ideas

In my previous blog, we wrote about implementing a management system. This boils down to sharing a common vision up and down and across the organisation, measuring progress, and pinning accountability on individuals. This time, we would like to talk about simple things that organisations can do to shrink their carbon footprints. But first let’s talk about the things that hold us back.

When we take on new clients we sometimes find that they are baffled by what I call energy industry-speak. We blame this partly on government. We understand they need clear definitions in their regulations. It’s just a pity they don’t use ordinary English when they put their ideas across in public forums.

Consultants sometimes seem to take advantage of these terms, when they roll words like audit, assessment, diagnostic, examination, survey and review across their pages. Dare we suggest they are trying to confuse with jargon? We created ecoVaro to demystify the energy business. Our goal is to convert data into formats business people understand. As promised, here are five easy things your staff could do without even going off on training.

  1. Right-size equipment? outsource peak production in busy periods, rather than wasting energy on a system that is running at half capacity mostly.
  2. Re-Install equipment to OEM specifications ? individual pieces of equipment need accurate interfacing with larger systems, to ensure that every ounce of energy delivers on its promise.
  3. Maintain to specification ? make sure machine tools are within limits, and that equipment is well-lubricated, optimally adjusted and running smoothly.
  4. Adjust HVAC to demand ? Engineers design heating and ventilation systems to cope with maximum requirements, and not all are set up to adapt to quieter periods. Try turning off a few units and see what happens.
  5. Recover Heat ? Heat around machines is energy wasted. Find creative ways to recycle it. If you can’t, then insulate the equipment from the rest of the work space, and spend less money cooling the place down.

Well that wasn’t rocket science, was it? There are many more things that we can do to streamline energy use, and coax our profits up. This is as true in a factory as in the office and at home. The power we use is largely non-renewable. Small savings help, and banknotes pile up quickly.

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The General Data Protection Regulation & The Duty to use Encryption

The General Data Protection Regulation, abbreviated to GDPR, raised a storm when it arrived. In reality, it merely tightened up on existing good practice according to digital security specialists Gemalto. The right to withhold consent and to be forgotten has always been there, for example. However, the GDPR brings a free enforcement service for consumers, thus avoiding the need for third party, paid assistance.

The GDPR Bottom Lines for Data Security
Moreover, the GDPR has penalties it can apply, of the order that might have a judge choking on his wig. Under it, data security measures such as pseudonymisation (substitution of identifying fields) and encryption (encoding including password protection) have become mandatory. Businesses must further respect their client data by:

a) Storing it in a secure environment supported by robust services and systems

b) Having proven measures to restore availability and access after a breach

c) Being able to prove frequent effectiveness testing of these measures.

The General Data Protection Regulation places an onus on businesses to report any data breaches. This places us in a difficult situation. We must either face at least a wrist slap upon reporting failures. Alternatively, pay a fine of up to ?10 million, or 2% of total worldwide annual turnover.

The Engineered Weak Link in the System
Our greatest threat of breach is probably when the data leaves our secure environment, and travels across cyberspace to an employee, stakeholder, collaborator, or the client themselves. Since email became open to attack, businesses and individuals have turned to sharing platforms like Dropbox, Google Drive, Skydrive, and so on. While these do allow an additional layer of password protection, none of these has proved foolproof. The GDPR may still fine us heavily, whether or not we are to blame for the actual breach.

How Hacking is Approaching Being a Science
We may make a mistake we may regret, if we do not take hacking seriously. The 10 worst data hacks Identity Force lists are proof positive that spending lots of money does not guarantee security (any more than having the biggest stock of nuclear weapons). We have to be smart, and start thinking the way that hackers do.

Hacker heaven is finding an Experian or a Dun & Bradstreet that may have shielded 143 million, and 33 million consumer records respectively, behind a single, flimsy cyber-security door. Ignorance is no excuse for them. They should simply have known better. They should have rendered consumer data unreadable at individual record level. The hackers could have found this too demanding to unpick, and have looked elsewhere.

How Data Encryption Can Help Prevent Hackers Succeeding
Encrypting data is dashboard driven, and businesses need not concern themselves about it works. There are, however, a few basic decisions they must take:

a) Purge the database of all information held without explicit permission

b) Challenge the need for the remaining data and purge the nice-to-haves

c) Adopt a policy of encrypting access at business and customer interfaces

d) Register with three freemium encryption services that seem acceptable

e) After experimenting, sign up for a premium service and be prepared to pay

Factors to Consider When Reaching a Decision
Life Hacker?suggests the following criteria although the list is a one-size-fits-all

a) Is the system fast, simple, and easy to operate

b) Can you encrypt hidden volumes within volumes

c) Can you mass-encrypt a batch of files easily

d) Do all other files remain encrypted when you open one

e) Do files automatically re-encrypt when you close them

f) How confident are you with the vendor, on a scale of 1 to 10

It may be wise to encrypt all the files on your system, and not just your customer data. We are always open to a hack by the competition after our strategic planning. If we leave the decision up to IT, then IT, being human may take the easy way out, and encrypt as little as possible.

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Introduction to Matrix Management

A leader is responsible to empower his people and get the best out of them. Yet an organisational structure can either help or hamper performance. Worst, it can make or break success.

Looking at the fast-changing world of the global economy, whatsoever slows up and obstructs decision-making is a challenge. Hierarchical management is rather unattractive and functional silos are unlikable. Instead, employees desire to create teams equipped with flexibility, cooperation and coordination.

Recognising that companies have both vertical and horizontal chains of command, the matrix model is created. The concept of this principle lies in the ability to manage the collaboration of people across various functions and achieve strategic objectives through key projects.

Consider this scenario:

Ian is a sales executive of a company. His role is to sell a new product under the supervision of a product manager. The manager is expert about the product and she is accountable to coordinate the people across the organisation, making sure the product is achieved.

Moreover, Ian also reports to the sales manager who oversees his overall performance, monitors his pay and benefits and guides his personal development.

Complicated it may seem but this set-up is common to companies that seek to maximise the effect of expert product managers, without compromising the function of the staffing overhead in control of the organisation. This is a successful approach to management known as Matrix Management.

Matrix Management Defined

Matrix management is a type of organisational management wherein employees of similar skills are shared for work assignments. Simply stated, it is a structure in which the workforce reports to multiple managers of different roles.

For example, a team of engineers work under the supervision of their department head, which is the engineering manager. However, the same people from the engineering department may be assigned to other projects where they report to the project manager. Thus, while working on a designated project, each engineer has to work under various managers to accomplish the job.

Historical Background

Although some critics say that matrix management was first adopted in the Second World War, its origins can be traced more reliably to the US space programme of the 1960’s when President Kennedy has drawn his vision of putting a man on the moon. In order to accomplish the objective, NASA revolutionised its approach on the project leading to the consequent birth of ?matrix organisation?. This strategic method facilitated the energy, creativity and decision-making to triumph the grand vision.

In the 1970’s, matrix organisation received huge attention as the only new form of organisation in the twentieth century. In fact it was applied by Digital Equipment, Xerox, and Citibank. Despite its initial success, the enthusiasm of corporations with regards to matrix organisation declined in the 1980’s, largely because it was complex.

Furthermore, the drive for motivating people to work creatively and flexibly has only strengthened. And by the 1990’s, the evolution of matrix management geared towards creation and empowerment of virtual teams that focused on customer service and speedy delivery.

Although all forms of matrix has loopholes and flaws, research says that until today, matrix management is still the leading approach used by companies to achieve organisational goals.

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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