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The “on the side” hustlers


In recent years, the trend of remote work has gained popularity, especially in the technology industry.

The advent of modern technology has seen certain kinds of employees no longer being required to be physically present in an office to perform their job functions.

This flexibility is praised by many as having benefits but also comes with a set of challenges, not just related to the intermingling of work and home life but also the shift of some of the real estate costs and costs typically associated with office-bound workers.

Benefits particularly lauded by those working remotely, are the avoidance of long commutes and of course health and safety concerns in times of pandemic.

One particular challenge for employers is the potential for employees to engage in “moonlighting”, which can be a significant concern for certain employers, especially in the technology industry. For the uninitiated, moonlighting refers to the practice of working a second job in addition to one’s primary job.

The origin of “moonlighting” dates back to the early 1800s, when it was commonly used to describe the practice of working at night by the light of the moon.

In the early 1900s, the term began to be used more broadly to refer to working a second job in addition to the primary job. Moonlighting became increasingly prevalent in the United States during the Second World War when workers were encouraged to take on additional jobs to support the war effort.

After the war, moonlighting continued to be a common practice, especially among blue-collar workers who were looking to earn extra income to support their families.

In the 1960s and 70s, moonlighting gained even more widespread acceptance as a way for employees to pursue their passions or supplement their income. However, during this time, moonlighting also became a great source of controversy, with some employers expressing concerns about conflicts of interest and decreased productivity.

With the rise of the “gig economy” in recent years, moonlighting has become even more prevalent, especially in industries like technology, where employees have in-demand skills that can be used for side projects and freelance work.

For employees, it’s a way to earn extra income or pursue their passions. For employers, it can create a conflict of interest and pose a significant perceived and actual risk to their business. In the tech industry, where employees have access to sensitive and confidential information for example, moonlighting poses the risk of unintentional or deliberate data breaches and this in turn jeopardizes a company’s reputation and introduces avoidable potential security risks.

An employee working on a project for a competing company may unintentionally share confidential information, leading to a data breach. Policies on personal use of equipment often mitigate this but things might also be said in conversations and in other work-related circumstances.

There are several reasons why tech workers may be particularly more prone to moonlighting. Firstly, the nature of their work often involves flexible hours and remote working arrangements, which can make it easier for them to take on additional work.

Secondly, the relative shortage of competent tech workers who are in high demand at a specific price point, and the skills they possess can be valuable to other companies.

From the employer’s perspective, it could be argued that there is the potential for decreased productivity, missed deadlines, and poorer quality of work as well as potential legal and previously cited reputational risks.

To mitigate the risks associated with moonlighting, employers often take contractual, policy, and control steps. Firstly, they may include moonlighting clauses in employee contracts, they may prohibit employees from taking on additional work without prior approval.

Monitoring and tracking systems may also be considered on work assigned equipment like keyboard and screen monitors to ensure that employees are not engaging in unauthorized moonlighting or behaviors. These systems not only monitor employee activity but also flag suspicious behavior, such as accessing unauthorized websites or sharing confidential information.

It’s a difficult balancing act, employees value the flexibility and freedom to pursue side projects, and a blanket ban on moonlighting can lead to increased staff turnover and decreased job satisfaction.

Employers can consider a more nuanced approach, such as allowing employees to engage in moonlighting as long as it doesn’t create a conflict of interest or compromise the company’s security though exactly how this is measured may be difficult to establish.

Complete prohibition of moonlighting altogether may seem like an easy solution but can also create some interesting disbenefits.

Employees disallowed from the pursuit of side projects or engaging in freelance work may feel very stifled and demotivated in their primary job. This may result in decreased job satisfaction and productivity, ultimately causing harm to the quality of their work and commitment to the business.

Prohibition can also lead to talent loss as employees not allowed to pursue side projects or freelance work may be more likely to seek employment elsewhere, where they have more flexibility and autonomy. Employers who prohibit moonlighting may find themselves struggling to attract and retain top talent as a result of this restrictiveness.

Side projects and freelance work can provide valuable indirect learning experiences that help employees develop new skills they can bring back to their primary job.

The prohibition of moonlighting can also create legal risks for employers. In some states and countries, laws protect employee rights to engage in lawful off-duty activities, which may include moonlighting. Employers who prohibit moonlighting without a clear and compelling reason may be at risk of legal action from employees.


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Author: Uli Lokshin

The future for ERP in 2023


Enterprise resource planning (ERP) software solutions have been a crucial tool for businesses of all sizes for several decades now.

ERP software like SAP, Oracle Business Suite, NetSuite and Microsoft Dynamics have helped organizations manage their resources more effectively, streamline operations, and make data-driven decisions.

As businesses have become more data-driven, the demand for easy-to-use tools to analyze and visualize data will increase. Consumer grade user experiences have become table stakes for ERP vendors trying to retain market share or garner attention from new audiences.

Tech advances, particularly cloud tech, and the accompanying business landscape do make the future of ERP software solutions uncertain.

Legacy on-premise ERP systems are also typically more expensive upfront, require specialized IT staff to maintain, and may have limited scalability. Upgrades and updates may also be more time-consuming and expensive than with cloud ERP.

The current trend in ERP software is towards more cloud-based solution adoption.

Cloud-based ERP software offers several benefits over traditional on-premises solutions, including reduced costs, improved scalability, and increased accessibility. With cloud-based solutions, companies no longer need to invest in expensive hardware, software, and IT personnel.

Cloud-based ERP solutions are also often highly scalable, allowing businesses to easily add or remove users and features as needed. Finally, cloud-based ERP solutions are accessible from anywhere with an internet connection, making them ideal for remote work and global operations.

Integration of artificial intelligence (AI) and machine learning (ML) capabilities is also increasingly becoming a part of the selection criteria and blockchain is considered to have some potential.

Both of these technologies can help businesses automate routine tasks, analyze vast amounts of data, and provide valuable insights. AI and ML help businesses identify patterns and trends that would often be difficult or impossible to discern manually. This, all in its turn, helps businesses make more informed decisions and optimize their operations for maximum efficiency.

The heritage ERP vendors are likely to continue to invest heavily in improving the user experience of principally their newer software most of which is cloud focused, to make it easier for business users to access and understand data.

One of the biggest challenges facing ERP vendors in this wave of forced techstack renewal is the need to balance flexibility with standardization. Customization of solutions that meet their unique needs has long been discouraged, it creates compatibility issues when integrating with other systems and makes the platform difficult to upgrade. ERP vendors are having to look long and hard at how they build to work out just how customizing can be adequately supported without becoming a nightmare of the future

Another challenge is the increasing demand for real-time data. Modern business practices are heavily data-driven, they have a need for real-time data to support agility and responsiveness. ERP solutions have often been bound up in batch based processes and now they have to find a way to provide real-time data without sacrificing data accuracy or system performance.

Cloud ERP and legacy on-premise ERP systems have their own advantages and disadvantages. It’s not a matter of one being “as good as” the other, but rather which solution is more suitable for a specific business.

Cloud ERP systems are becoming increasingly popular because they offer several benefits, such as lower upfront costs, scalability, accessibility, and automatic updates. With cloud ERP, businesses don’t need to worry about hardware maintenance or software updates, as the cloud provider takes care of everything.

Nucleus Research provides a ERP Value Matrix as a tool developed by them to evaluate ERP vendors and solutions based on two primary factors: usability and functionality.

The matrix places ERP vendors in one of four categories: Leaders, Experts, Facilitators, or Core Providers, based on how they perform on these two factors. The matrix also takes into account other factors such as total cost of ownership (TCO), customer support, and innovation, to provide a comprehensive evaluation of each vendor.

The matrix provides businesses with an objective assessment of ERP vendors, helping them to identify which vendors and solutions are the best fit for their needs. By evaluating vendors based on their usability and functionality, businesses can better understand how each solution will impact their operations, and choose the solution that provides the best value for their organization.

The research offers two angles also, a SMB ERP Technology Value Matrix and the Enterprise ERP Technology Value Matrix for business targeting organizations with over $500M in annual revenue. The last assessment was mid 2022 and another is likely June 2023.

Credit: ERPSoftwareBlog

Some of the more popular heritage ERP solutions are also offered as ERP solutions but its worth considering the main players in the cloud space right now.

Acumatica – Acumatica’s cloud ERP solution is designed to provide a flexible and customizable platform for small to mid-sized businesses, delivering real-time insights and improving business efficiency.

Epicor ERP – Epicor’s cloud ERP solution combines industry-specific functionality with a modern cloud delivery model to help manufacturers grow their business and streamline their operations.

Microsoft Dynamics 365 – Microsoft Dynamics 365 is a cloud-based ERP system that offers a range of modules for financial management, supply chain management, and project management. It also integrates with other Microsoft products such as Office 365 and Power BI for advanced analytics.

NetSuite – NetSuite’s cloud ERP solution provides businesses with a single, integrated platform for financial management, supply chain management, and CRM, helping to improve business efficiency and accelerate growth.

Oracle Cloud ERP – Oracle Cloud ERP is a cloud-based ERP system that provides a range of financial management, procurement, project management, and supply chain management tools. It also offers analytics capabilities and integrates with other Oracle cloud products such as Oracle HCM and Oracle CX.

Plex Systems – Plex Systems’ cloud ERP solution is designed specifically for manufacturing organizations, providing real-time insights into production processes and supply chain operations.

Rootstock Cloud ERP – Rootstock’s cloud ERP solution is built on the Salesforce platform and provides a range of manufacturing, supply chain, and financial management tools for businesses of all sizes.

Sage Intacct – Sage Intacct’s cloud ERP solution is designed for small to mid-sized businesses, providing a range of financial management and accounting tools that are customizable and scalable.

SAP S/4HANA Cloud – SAP S/4HANA Cloud is a cloud-based ERP system that provides a range of modules for financial management, procurement, sales, and distribution. It also provides advanced analytics capabilities and is built on the SAP HANA in-memory database platform.

Workday Financials – Workday Financials is a cloud-based ERP system that provides a range of financial management tools, including accounting, procurement, and financial reporting. It’s designed for medium to large enterprises and offers real-time insights into financial performance.

Security concerns, potential downtime, and limited customization options are likely to remain ongoing concerns. Those businesses that require highly specialized or industry-specific functionality may find that a cloud ERP system simply doesn’t meet their specific needs and many on existing on-premise platforms will struggle to make the migration to the cloud.


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Author: Clinton Jones

More of the same, ten years on


In 2012, a wave of layoffs swept across various industries and companies worldwide, leaving thousands of employees without jobs. These layoffs were a result of economic downturns, mergers, acquisitions, and restructurings. This in turn led to a recession. The recession led to reduced consumer spending and lower corporate profits and layoffs. These had a significant impact on the lives of many, their families, and their communities.

It’s 2023 and we are seeing the news filled with much of the same tone and sentiment and news but the brands are many that have never had layoffs before. 395 tech companies with 108986 employees laid off at the time of writing, according to layoffs.fyi. In 2022, there were 1,535 layoffs at tech companies w/ 241,176 people impacted according to a similar tracker site trueup.io

In 2022 Morgan Stanley start with announcing a workforce reduction by 2%, Buzzfeed (12%), and PepsiCo plans for “hundreds” of jobs cut, Redfin (13%), Lyft (13%), Stripe (14%), Snap (20%), Opendoor (18%), Meta (13%), and Twitter (50%).

Sandra J. Sucher and Marilyn Morgan Westner wrote in What Companies Still get Wrong about Layoffs and also in A better, Fairer Approach to Layoffs in HBR  about how short-term cost savings achieved through layoffs are often overshadowed by bad publicity, loss of knowledge, weakened engagement, higher voluntary leavers, and reduced innovation — all hurtful to long term profits.

Layoffs are a harsh reality of the business world, and while they are often necessary to maintain the financial viability of a company, they can be incredibly damaging to those who lose their jobs. The impact of layoffs goes beyond the loss of income; it can result in a loss of self-worth, a sense of isolation, and a feeling of betrayal. Many employees who have been laid off find it challenging to find new jobs in their fields, and the loss of benefits, such as healthcare and retirement plans, can have long-lasting effects.

The 2012 layoffs were particularly devastating because they occurred during a time of economic uncertainty namely the global economic downturn that had begun in 2008.

Many people were already struggling to make ends meet, and losing their jobs only compounded their difficulties. The layoffs affected a wide range of industries, including manufacturing, finance, and technology companies such as the Bank of America, retailer JCPenney, and tech behemoth Yahoo.

Many companies also faced increased competition from emerging markets, which put additional pressure on bottom lines.

The trend of mergers and acquisitions around that time, focused on increase efficiency and reduce costs, which often meant eliminating redundant duplicative positions and streamlining operations.

Of course, some companies laid off employees as part of a broader restructuring plan, a necessary position for any company focused on future growth or to address specific challenges, such as declining sales or a shift in consumer demand.

Layoffs are a difficult but necessary reality in business, but companies have a responsibility to treat their employees with respect and dignity during the process; often this is not the case. HR departments and managers are often quite poorly equipped to deal with layoffs.

Part of the approach of any layoff is to provide clear communication about the rationale for layoffs, offering outplacement services to help employees find new jobs, and providing fair severance packages accompanied by empathy and respect. Companies that handle layoffs poorly risk reputation damage and loss of trust among the “survivor” employees and of course the impact on customers. Unfortunately more than ten years later we’re seeing some of the same mistakes being made in the way layoffs are being handled.

The memory of 2012 is perhaps still clear and present in the minds of many that were impacted and some are seeing this again today. with the current round of layoffs. They’re all a painful reminder of the fragility of the job market and the importance of preparing for economic uncertainty.

One cannot help feeling that the root cause of a lot of these layoffs is tied to poor planning and organizational management, but there may be a more opportunistic seedy underbelly to some of the layoffs.

It’s likely that we’ll see a number of cascading effects, particularly among employees who have been hit twice by economic downturn layoffs and of course among those for whom this is the first time they have ever been laid off.


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Author: Jewel Tan

different types of bar glasses with colored liquids
Customer master data management – the data types

Depending on the nature of your business and the relationship that you have with your customers you may have several different types of customer master data that you choose to manage and maintain. There are other types of customer data that you may need to manage too, data types that you don’t necessarily always think of as master data but which may benefit from being stored and retrieved centrally as required.

Quantitative and Qualitative

Typically, you can think of customer data as falling into one of two camps, either qualitative or quantitative. So what is the difference?

If you think of this in the context of survey data, for example, quantitative data is values that are representative summations or counts. Each data element is exclusively numerical. The values are quantifiable and can be used in statistical and mathematical analyses and calculations. They’re certain quantities, amounts or ranges. Typically they are also accompanied by measurement units such as kilos, years, metres etc. In the case of say, the height of a person. It makes sense to set boundary limits (validity ranges) to such data. It may also be useful to apply arithmetic operations or calculations to that data, like converting to an alternative unit of measure.

Coffee Club Schema

As for qualitative data, in master data for customers, in particular, this may be data values like sizing standards – S for small, M for medium and L for Large and so on. Others might be colours, preferences, types assortments etc. As long as numbers are not assigned, even though they may equate to numbers, this is likely considered qualitative. Similarly, the country, state or province in which a person claims to be a resident is qualitative because the indicator is an attribute characteristic.

Now you might ask, why would I care about whether this is quant or qual? The answer may lie in how you do your segmentation and reporting. When you are dealing with numeric values it is a great deal easier to create reports and extracts of data and to select ranges in particular if you are using quantitative data. You could for example have people defined as young, youthful, middle-aged, old or ancient but that’s not as useful as knowing the actual age. This is particularly important if I want all people over 18 and less than 80 for example. In addition, I could potentially calculate who these people are if I know their date of birth.

Declared and Inferred

Now that we have distinguished between quant and qual, it is worth also considering data that is inferred vs declared. Declared data is much more definitive, much more absolute at a point in time when compared with inferred data. Often the declared data is provided by the customer themselves or acquired from a system or provider that they may have provided that data to.

Inferred data is conversely derived. It may, for example, be the result of combining data from one or more sources and then effectively joining the dots between data points to draw some sort of conclusion.

Again, you might question, why you would care. The main reason might lie in the fact that your business needs to know the basis on which you hold and maintain customer data and then also consider how you arrive at decisions based on that data.

Coffee Shop In Store Schema

Data privacy matters continue to evolve, from Europe’s General Data Protection Regulation (GDPR) to the UK’s equivalent and Brazil’s Lei Geral de Proteçao de Dados (LGPD), Australia’s Privacy Act, the California Consumer Privacy Act (CCPA), Japan’s Act on Protection of Personal Information, South Korea’s Personal Information Protection Act, Thailand Personal Data Protection Act (PDPA), New Zealand’s Privacy Act, India’s Personal Data Protection Bill (PDPB), South Africa’s Protection of Personal Information Act (POPIA), The People’s Republic of China publicly released draft of the Personal Data Protection Law, PDPL and several others. It is important to recognise the approach that your business has to data collection. Data, personal data in particular is an emotionally charged topic with changes in consumer opinion ever constant.

Declared Data willingly shared by the user through form-fills, cookie opt-ins and submissions through social media accounts often carries the highest value to different aspects of your business as this data is 100% based on the customer or prospect’s activity. Ideally, you will also have gathered a consent indicator from the person who provided this data, which can help inform you on how this data can be used. Optimally, error-free barring deceit on the part of the submitter, you may use this data to determine appropriate access to certain products and services that you offer.

Inferred is often considered amongst the most contentious of data because as the name suggests, you’re joining dots. Data like this is engineered or developed. It has been created without express input from the person that it relates to, it may be systematically generated based on transactions, or activity. This data is neither better, nor worse than declared data, it is simply different and is most contentious, often because it is calculated algorithmically and is based on assumptions, perhaps well-informed, but nonetheless, not declared by the person that they relate to.

You might have a customer who declares that their preferred beverage is coffee but you often see tea or chai in their orders. Does that tell you that they lied? Well no, they have declared their preference to be coffee but they may often order other beverages for others in their party and that’s why you’re seeing an anomaly. You have derived a preference perhaps, from all their known transactions but that doesn’t make your inferred data correct.

So, you have these classes of data, but now let’s consider other aspects of the data that you may have.

Basic data and the rest

This is a very subjective discussion. The main reason is that what one company may consider basic customer data may be considered much more than another company may need. The decision as to what you choose to create and maintain and the reasons you may define the data in different ways may vary wildly from the needs and expectations of a competitor or another industry or even a use case within your organization.

Pretectum’s Customer Master Data management system (CMDM) doesn’t prescribe what you should or should have as that basic data definition, it is entirely up to you. While we may offer some standard models (schemas) and your systems may have specific minimum requirements, those can be supported but the end decision is up to you.

A coffee shop may only need an email address and a first name to maintain their loyalty card or loyalty system. A retailer on the other hand may require a full customer name, phone number, email address, gender, and addresses in order to make deliveries etc. A bank may require much more, not just for the purposes of giving the customer a great experience, but also because it may be a legal requirement.

JUTLAND COFFEE COMPANY

When you embark on the implementation of your master data management solution, these are some of the aspects that you might want to consider.

Either way, Pretectum’s CMDM is able to support you in leveraging all of these different ways of deciding what to store and what the criteria are around the values that you might store, qualitative, quantitative, declared or inferred. All types of data are supported in a highly configurable way according to your specific business needs.

If you’re wondering whether you can achieve a particular outcome in your use of the Pretectum master data management system to improve sales, support a particular initiative or simply provide your customers with a great personalized customer experience, reach out to us and we’ll tell you what you need to know about how the system can help.

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10 CUSTOMER DATA ROLES IN CUSTOMER RELATIONSHIP MANAGEMENT

Customer data plays a crucial role in customer relationship management as it provides valuable insights into customer behavior, preferences, and interactions with your organization.

Having accurate and up-to-date customer data can help your organization better understand consumers and provide personalized experiences that foster loyalty and improve satisfaction and confidence in your products or services.

Harvard Business Review contributor and business expert Barbara Bund Jackson has found this is very valuable through her research.

Here are a few ways in which customer data can impact your relationship with the customer:

Personalization: By making customer data an integral part of as many customer journeys as possible, you’re able to tailor customer interactions, providing experiences that are targeted and specific to the individual customer needs and interests.

Increased efficiency: Customer data can help to streamline your business processes and help to make better use of your resources. Routine task automation like these can benefit from a direct relationship with actual customer data

Marketing and Sales Lead scoring: Automated lead scoring systems use algorithms to evaluate leads based on their likelihood of becoming customers, and prioritize them for follow-up by sales teams. Here you might use past transactional history or simply the attributes of the customer like age and gender but through zero-party-data may be able to hone your lead scoring further.

Marketing automation: Marketing automation tools automate routine marketing tasks, such as email campaigns and social media posts, and allow companies to personalize marketing efforts based on customer data. Here, simple knowledge of the customer name, their address and other contact information, is helpful. This is especially true if that data is maintained by the customer through self-service.

Customer service automation: Customer service automation tools, such as chatbots and self-service portals, allow companies to automate routine customer service tasks and provide faster, more efficient customer support. Integration with known customers and their data, can make the dialog and interaction much more personal and directed.

Sales automation: Sales automation tools automate tasks such as lead management, opportunity tracking, and sales forecasting are used to free up sales teams to focus on more high-value activities. The more data there is in the customer master, the more effective these automations are.

Workflow automation: Workflow automation tools are used to automate repetitive tasks and processes, such as the routing of customer inquiries to the appropriate team members, freeing up time for customer-facing employees to focus on more high-value activities. The more attributes you attach to the customer master the more precision and control you have in directing these interactions and workflows.

Improved decision-making: Customer data provides valuable insights into customer behavior, preferences, and feedback, which can help companies make better-informed decisions about product development, marketing, and customer support.

Better understanding of customer needs: Customer data can help companies better understand their customers’ needs, pain points, and areas for improvement, which can lead to improved customer experiences and increased customer satisfaction.

Increased customer loyalty: It should come as no surprise that Pretectum thinks loyalty is so intrinsically linked to customer data, that we use #loyaltyisupforgrabs prolifically in social media. By providing personalized experiences and demonstrating a commitment to understanding and meeting the needs of their customers, companies can increase customer loyalty and reduce customer churn.

Customer data is a critical component of effective customer relationship management and can have a significant impact on customer relationships, customer satisfaction, and business success. Pretectum feels a CMDM is the best way to serve up the data to business applications.

The fast track to the Z-List


We’re probably all comfortable with the concept of an A-list celebrity, but what about the Z-Lister?

The concept of a Z-lister refers to a person who is considered to be at the very bottom of the celebrity hierarchy. These individuals are often seen as being irrelevant, unknown, or unimportant in the entertainment industry. They are typically not well-known outside of their niche area of expertise, and often struggle to maintain any kind of mainstream attention or recognition.

The term “Z-lister” is used to describe individuals who are typically ranked at the lowest level of celebrity status. This can include reality TV stars, social media influencers, or other minor celebrities who have limited influence or following. While some may have a small dedicated fanbase, they often lack the recognition and status of more established celebrities.

The concept of the Z-lister has become increasingly prevalent in the age of social media and reality TV, where it is easier than ever to become a public figure. With the rise of platforms like Instagram, TikTok, and YouTube, anyone can potentially gain a large following and some degree of notoriety. However, this also means that there is a much larger pool of aspiring celebrities, and it can be difficult to stand out from the crowd.

The term Z-lister can be seen as somewhat derogatory, as it implies that the individual in question is of little significance or importance. It can also be seen as a reflection of our celebrity-obsessed culture, where status and fame are highly prized, and those who fail to achieve these goals are often seen as losers or failures.

However, it is worth noting that not all Z-listers are unsuccessful or irrelevant.

Some may be highly successful within their niche area of expertise, and may have a dedicated fanbase or following. Others may be using their minor celebrity status as a stepping stone to greater success, or may simply enjoy the attention and recognition that comes with being a public figure.

Ultimately, the concept of the Z-lister is a reflection of the changing nature of fame and celebrity in the modern world.

While it is now easier than ever to gain a degree of public recognition, it is also harder than ever to stand out from the crowd and achieve lasting success.

The rise of social media and reality TV has created a vast and diverse landscape of celebrities, from A-listers to Z-listers and everything in between, and it is up to each individual to determine what level of fame and recognition they are comfortable with.


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Author: Jewel Tan

Playing at work


It has been a while since a colleague raised their eyebrows at me and my light-hearted disposition to work. But make no mistake, work itself is serious stuff but it doesn’t have to be boring and dull if you tackle it with the right mindset.

The idea that work should be considered as play might seem counterintuitive at first glance. We typically associate play with leisure and work with productivity and output. However, there are many compelling reasons to consider work as play, and doing so can lead to a more enjoyable and fulfilling work experience.

When we think of play, we think of activities that we enjoy and look forward to doing; the same can be true for work if we approach it with a positive mindset. By finding ways to make work enjoyable and engaging, we can change our perception of work from something that we have to do to something that we really want to do.

Albert Einstein is often quoted as saying, “Play is the highest form of research.” This statement suggests that Einstein believed that play was not only enjoyable but also an important part of the learning and discovery process. Einstein also believed that work and play were not mutually exclusive, and that one could approach work with a playful and creative mindset.

In addition to his famous quote, Einstein also wrote about the importance of play in his personal life. He enjoyed playing the violin, sailing, and hiking, and he often credited his hobbies with helping him to think creatively and come up with new ideas. Einstein believed that play was a way to stimulate the imagination and that it could lead to new insights and discoveries.

Play is also often associated with creativity and innovation; when we engage in play, we are more likely to experiment and try new things, which can lead to new ideas and insights. Similarly, when we approach work with a playful mindset, we are more likely to come up with creative solutions to problems and find new ways to approach complex and simple tasks.

Play fosters intrinsic motivation such that when we engage in play, we do it because we enjoy it, not because we expect to get a reward or avoid punishment. Similarly, when we approach work as play, we are more likely to be intrinsically motivated to do our best possible work. We are not just working for a paycheck or promotion, but because we enjoy the work itself.

Many considered play a social activity, one that can help build relationships and foster a sense of community. Similarly, when we approach work with a playful mindset, we are more likely to build positive relationships with our colleagues and enjoy working together. This can lead to a more supportive and collaborative work environment.

Play is a great way to reduce stress and promote relaxation, many a keen sportsman will take to the golf course or the outdoors to destress. Similarly, when we approach work with a playful mindset, we are more likely to feel less stressed and more relaxed. This can lead to a more positive work environment and improved overall well-being.

There are many reasons why work should be considered play.

By finding ways to make work enjoyable and engaging, we can approach work with a positive mindset and enjoy the work itself.

Approaching work as play can foster creativity, build relationships, reduce stress, and promote intrinsic motivation.

As we spend a significant portion of our lives at work, it is essential to find ways to make work more enjoyable and fulfilling. By considering work as play, we can achieve this and create a more positive and productive work experience.


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Author: Clinton Jones

You can’t work from home


While the rise of remote work and hybrid working models have made it possible for many employees to work from home, there are still some types of work that are not suitable for remote work.

Some jobs require specific equipment or tools that are not easily accessible outside of the workplace, while others require close collaboration and communication with colleagues.

Some jobs require specialized equipment, such as manufacturing or laboratory work, which cannot be easily transported or replicated in a home environment.

For example, a chemical engineer who works in a lab may require access to specific materials and tools that are not available at home, making it impossible to work remotely.

Some jobs require a physical presence, such as those in the hospitality or healthcare industries. For example, a nurse cannot provide care to patients from home, and a restaurant worker cannot prepare and serve food remotely.

Some jobs require frequent face-to-face interaction, such as those in sales or customer service. For example, a salesperson may need to visit clients in person, and a customer service representative may need to speak with customers directly to address their concerns.

Some jobs require close collaboration and communication with colleagues, such as those in research and development or project management. For example, a team of engineers working on a new product may need to work together in person to share ideas, troubleshoot problems, and make decisions.

Client-facing interactions jobs, such as those in the legal or financial industries may preclude working from home. For example, a lawyer may need to meet with clients in person to discuss legal matters, and a financial advisor may need to provide advice to clients face-to-face.

There is also a class of jobs that require on-site supervision. These jobs require on-site supervision, such as those in construction or manufacturing. For example, a construction worker needs to be supervised by a manager who can oversee the work and ensure that it is done safely and effectively.

While remote work and hybrid working models have made it possible for many employees to work from home, there are still some types of work that are not suitable for remote work.

Jobs that require specialized equipment, physical presence, frequent face-to-face interaction, team collaboration, client-facing interaction, and on-site supervision are among the types of work that are not suitable for working from home.

Organizations need to assess the requirements of each job role and determine whether it can be done remotely, on-site, or in a hybrid model to ensure that employees can work effectively and efficiently.


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Author: Flaminio

What Is Apache Airflow


  Apache Airflow is an extremely popular tool that data engineers rely on. But why? Why do data engineers like Airflow? Also, what does the Apache Airflow event do? In this article, we will answer questions like: What is Airflow? What is a DAG? Why do people use Apache Airflow? Why do we like Airflow?…
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The post What Is Apache Airflow appeared first on Seattle Data Guy.


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Author: research@theseattledataguy.com

Do You Need A Data Warehouse – A Quick Guide


Recently several consulting calls started with people asking, “Do we need a data warehouse?” This isn’t a question about whether you need data warehouse consultants, but instead whether you should event start a data warehouse project. Which is a very fair question. Not every company needs a data warehouse. That being said data warehouses can…
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The post Do You Need A Data Warehouse – A Quick Guide appeared first on Seattle Data Guy.


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Author: research@theseattledataguy.com

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