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.

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How AI Helps Improve Field Service

Its seems that with the current rate of technological innovation that these is something new every single day.  Therefore, you’re always looking forward to a new technological innovation that’s going to help you make your business operations more efficient and automated.

One of the most fascinating milestones in the field of technology is the integration of Artificial Intelligence (AI) in business. In one way or the other, AI gives a glimpse of machine supremacy that allows computers to perform tasks that were initially performed by humans. 

Are machines going to completely replace people in the workplace?

Of course, not.  Technologies like AI and Machine Learning are designed and meant to support employees in doing their tasks too boost their productivity.

AI is predominantly used to eliminate jobs and tasks that humans find boring, demotivating or monotonous. In some cases AI is also used to do jobs that are considered dangerous for humans to preform.

Previously the most common implementations for AI were all about gaming, entertainment, and advanced science,  now it’s spreading into a number of industries including the field service industry.

FieldElite – Field Service Software , can help you optimise the day-to-day operations of your business.

AI in field service management will enhance you business capabilities with:

  • Information Sharing
  • Real Time Updates
  • Automated Workflows
  • Digital Form Data Collection
  • Data Analysis

Improved Customer Service

For Service Based companies, customer retention is vital. Primarily because It can be 5-25 times more costly to acquire a new customer than it is to retain an existing ones.

Therefore customer retention should be a primary focus.? The good news is that by making use of AI you can implement services It can be 5-25 times more costly to acquire a new customer than it is to retain an existing one.

Staying on top of and ensuring you satisfactorily address and meet you customer demands and expectations can be a daunting task.? It can also be an expensive one,? especially for small field service based businesses like :

  • Heating & Plumbing Engineers
  • Electrical Contractors
  • Fire Safety Inspectors
  • HVAC Engineers
  • Facility Management
  • Building, Construction & Trade

Implementing Artificial Intelligence and Machine Learning to automate mundane and repetitive customer administration tasks will enable your staff to be free to provide additional value added tasks for your customers. Making your customers happier.

?Think about the active Chatbots. You can always get complaints directly from customers and address them right away.??

If at any point the customer is unhappy with your services, they can always raise the issue via the Chatbots. Since the bots contain necessary customer information, you can always get back to them and fix the issue at hand.?

With AI in field service, you can solve problems before they arise, or what is otherwise known as predictive maintenance,? In that way, you’ll have better customer relations because you’ll be able to address your customer concerns before they even become aware of them.

Improved Productivity

Scheduling tasks and managing the workforce isn’t a walk in the park. It goes beyond assigning tasks to your team members in the field and giving them deadlines to meet. Whether it’s a small firm or a big organisation, it’s quite difficult to organise the workforce.?

However, adopting Artificial Intelligence can iron out the difficulties most field organisations face in scheduling and managing tasks. Some years back, most firms relied on human intelligence to dispatch jobs to the right people based on given conditions. This was quite difficult, especially that it wasn’t always successful. But thanks to AI. With field service apps like FieldElite scheduling tasks and managing workforce is only a few clicks away.?

What’s more? There?s no room for error. Therefore, you’ll always match the right people for the job. Again, your team will always get tasks on time. That means, the job completion rate will go up, and hence the workforce becomes more productive.?

Predictive Maintenance

Usually, most business operations are based on ?solve the problem as it occurs?, which is just OK. However, it’s not always safe to wait until a problem occurs so that you solve it. Prevention is better than cure, and that’s why Artificial Intelligence comes handy in Field Service.

Using FieldElite Workforce Management Software , you don’t have to wait until something breaks.? Utilizing AI in field service enables you to proactively address field service needs and prevent unforeseen failures and interruptions.?

The ability to predict field service needs through field service apps like FieldElite enables you to make more accurate forecasts. In this way, resource planning is made easier, and as such, you’ll have smoothly running workflows. Again, by taking care of unforeseen circumstances in advance, you’re flexible enough to take care of the unexpected. And that means the overall productivity of your business will go up.

Job Management

Most field service jobs involve multiple stages that can take several days to complete. In addition to this, more often than not, you have to coordinate lots of equipment and contractors at the same time. All these can’t be achieved solely by human efforts. For more successful outcomes, it’s important to incorporate Artificial Intelligence in your field service operations.?

FieldElite is the field service solution that can help you manage sophisticated tasks. The app is packed with field service management tools that enable you to assign complicated tasks and keep track of your field techs. For long-cycle jobs, FieldElite app enables you to follow up on the activities going on the field to ensure they’re completed.?

With AI, there?s no room for error even when the jobs become more sophisticated.

Data Analysis

?

Field service industry involves lots of data. Some years back, organisations depended on human intelligence to analyse big data. Well, things still worked out, but as a human is to err, the outcome wasn’t always perfect. However, with Artificial Intelligence data analysis, 100% accuracy in data analysis is achievable. Field service solutions like FieldElite provide sophisticated data analytic tools that enable you to crack massive data and offer accurate solutions.?

FieldElite data analytics capabilities give you an insight into what’s not working and what needs to be improved. In that way, you can always address matters arising and take care of the loopholes.?

It’s time to go paperless with field management software like FieldElite if you?d like to make your business more profitable. Apart from improving the productivity of your workforce, incorporating AI in your business increases profitability. If you’re still doing your usual field rounds with a clipboard, it’s time to simplify your task with FieldElite app.?

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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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New Focus on Monitoring Soil

There is nothing new about monitoring soil in arid conditions. South Africa and Israel have been doing it for decades. However climate change has increased its urgency as the world comes to terms with pressure on the food chain. Denizon decided to explore trends at the macro first world level and the micro third world one.

In America, the Coordinated National Soil Moisture Network is going ahead with plans to create a database of federal and state monitoring networks and numerical modelling techniques, with an eye on soil-moisture database integration. This is a component of the National Drought Resilience Partnership that slots into Barrack Obama?s Climate Action Plan.

This far-reaching program reaches into every corner of American life to address the twin scourges of droughts and inundation, and the agency director has called it ?probably ?… one of the most innovative inter-agency tools on the planet?. The pilot project involving remote moisture sensing and satellite observation targets Oklahoma, North Texas and surrounding areas.

Africa has similar needs but lacks America?s financial muscle. Princeton University ecohydrologist Kelly Caylor is bridging the gap in Kenya and Zambia by using cell phone technology to transmit ecodata collected by low-cost ?pulsepods?.

He deploys the pods about the size of smoke alarms to measure plants and their environment.?Aspects include soil moisture to estimate how much water they are using, and sunlight to approximate the rate of photosynthesis. Each pod holds seven to eight sensors, can operate on or above the ground, and transmits the data via sms.

While the system is working well at academic level, there is more to do before the information is useful to subsistence rural farmers living from hand to mouth. The raw data stream requires interpretation and the analysis must come through trusted channels most likely to be the government and tribal chiefs. Kelly Caylor cites the example of a sick child. The temperature reading has no use until a trusted source interprets it.

He has a vision of climate-smart agriculture where tradition gives way to global warming. He involves local farmers in his research by enrolling them when he places pods, and asking them to sms weekly weather reports to him that he correlates with the sensor data. As trust builds, he hopes to help them choose more climate-friendly crops and learn how to reallocate labour as seasons change.

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