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“Data is the new oil.”

Unless you have been living under a rock for the last 15 years, you have probably heard the phrase “data is the new oil.” It was 2006 when Clive Humby, a mathematician and entrepreneur originally coined the phrase – and it has been echoed by thousands ever since. 

Clive Humby probably never expected this phrase to make such a lasting impression but it really was the perfect comparison. Oil and data have a lot in common.

Look around you, in some way or another, oil has played a crucial role in the existence of everything around you. Many everyday items are a product of oil, they are manufactured in a factory powered by oil, then transported by vessels which are also powered by, you guessed it, oil. 

Today, data is making just as much of an impact. Data is used in a multitude of ways that influence decision making in government, public policy, healthcare, science, and of course business.

Society relies on data and oil to make things go. For that reason they are considered valuable commodities – that many governments, policy makers and businesses are desperately trying to get their hands on. Data and oil are power. Without them, making things happen can be challenging. 

Most importantly, when we drill for oil or mine for data, to do so successfully requires some knowledge and the right tools. Otherwise it could be a colossal waste of time and resources. To drill for oil requires knowledge of where the oil might be and how to extract it. It requires machinery, and man power. Once the oil has been extracted, it needs to be refined so it can be used in its full potential. 

The same goes for data. There must be knowledge of where to collect data and how to extract it. It requires specific technology and manpower. Then once the data has been collected, it needs to be refined so it can be used to its full potential. 

Unlike drilling for oil, you won’t break your back trying to collect data. But it does require some effort. Collecting data is the first step in answering those valuable questions before we can refine it and get its true value. 

Here are some best practices for collecting data:

Have a robust internal system:

Collecting data in-house is the best practice when solving internal business challenges or identifying opportunities. To collect data in-house means that information is being recorded and stored internally on a consistent basis. Typically data is collected and stored in a customer relationship manager (CRM). And if your team is using your CRM, you probably have a pretty decent set of data to get insights from. If they aren’t using the CRM to its full potential – you should really consider it. Having some data, even if it is incomplete, is better than having no data at all. 

If you are not sure what to collect, it is still a great practice to capture as much data as you can. It’s never possible to know exactly what’s going to be of value in future. So collecting data in a structured format that can be translated into information and insights down the road and can create new opportunities in the future. And the good news is that data storage is cheap these days, so holding onto that data isn’t going to make much of a dent in your budget. 

Buy data from third parties:  

There are times when a company is unable to collect their own data because they could be a start-up, a company looking to enter a new market, or there is a major gap realized in the current set of data. Instead of starting from scratch, buying data from third parties is a good option. There are plenty of  data sets out there that third party data brokers have carefully taken the time to put together. They have a wide variety of data sets that are usually made up of data that is challenging to collect, data that is challenging to access, or very large sets of data – that could take decades to collect.

If you aren’t sure where to start, Quandl and Explorium are reputable data brokers with plenty of data to go around. 

Use third parties to buy training data: .

If you are looking to partake in the AI and Machine Learning boom and want to take on a project, the algorithms are going to require some training data to learn from. If there is a shortage of training data available, third parties are also a good solution for this as well. Third parties can provide data sets a lot faster and efficiently rather than trying to put together a set of training data

There are many options for training data, check out Hive, Scale, NTT Data, or Weights and Biases.

Use third parties to collect training data:

There are times where third party data brokers don’t have the exact set of data needed to answer that million dollar question. When specific data is needed but maybe your team doesn’t have the manpower, tools, or time to collect data there are third parties that can collect that data for you. Once again, long behold the third party data collectors. One of the most popular examples of this is Amazon Mechanical Turk. A platform that individuals from around the world collect data based on the instructions they have been provided with. 

Scrape data off the internet:

As everyone is aware — there is a lot of data on the world wide web, readily available at the tips of our fingers. This practice does require some expertise to create specific tools. But once that has been handled, very specific data can easily be scraped off the internet, parsed and used accordingly. Please be respectful of the terms and conditions of where you scrape data from though! Only do it if you allowed to do.

For example, something that our team has been successful at while scraping data off the internet for lead generation. Instead of sales reps spending hours prospecting qualified leads, our team created a tool that scrapes data off service providers websites such as lawyers and accountants to generate leads. The information was parsed and then put directly into the CRM to be accessed by the sales team. With the right expertise, a tool can be created to collect data on anything and be used to answer that million dollar question.

Ready, set, mine.

The top two reasons that businesses don’t collect data is because it appears to be either too intimidating or time consuming. What this really comes down to is not seeing value and the potential prosperity that could be uncovered. Data drives decision making and uncovers new opportunities. If data collection isn’t a priority, opportunities and insights are being left undiscovered, while challenges are being left unaddressed – both now and in the future. Which can equate to hundreds of thousands of dollars slipping through your fingers.

Collecting data is the easiest part of the process, especially with a little bit of guidance. Refining it is where things can start to become a bit trickier. Luckily, there are data experts out there who can help you uncover the true value of your data.

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Plus ça Change, Plus C’est La Même Chose

Jean-Baptiste Alphonse Karr

In case you don’t speak french (or you forgot almost everything you learned in highschool – looking at you Canadians!). The timeless proverb; “the more things change, the more they stay the same” implies that no matter what turbulent changes we experience, the status quo is reinforced. 

Our first thought jumped to sales operations. Sales ops has come a long way over the last few decades. Before, when many of us thought about sales the first thing that popped into our head was a sleazy, used car salesman, trying to nickel and dime you at every corner. Or the guy in the fedora, going door to door, selling the next best vacuum or tupperware set. Heck, even over the last year we have seen a major shift in sales operations from in-person to almost exclusively meeting our prospects over Zoom. 

Our point is, the sales process has changed a lot over time. And regardless of all the trends and changes in the market, sales operations has always been about selling better, selling faster and selling more. This is a capitalist market-driven economy after all. 

Sales Ops in 2021

It is fair to say that sales has become more difficult over the past few decades. 

Information is more widely available. Competition is stiffer. And for that reason, the modern customer has higher expectations and there must be a sense of trust before a purchase is made. Creating strong honest relationships is crucial to driving sales in the modern day. 

We are also living through the 4th technological revolution. Technology has swept through sales operations and has streamlined many of our day to day processes. Seems like there is a service or a tool for anything you could ever imagine. Then you blink and somehow, somebody has created another tool to make your business even more efficient. 

Despite all the amazing software services and solutions out there, many sales teams are still living in the stone age. Otherwise known as… superstar culture. 

Superstar Culture Sales

Is highly individualistic. It relies on a couple people to carry the team to the sales quota. Energy and resources are poured into the few sales wizards that seem to hold the world on their shoulders. Meanwhile, the rest of the sales team is not being given the support needed to improve their processes.

This culture is bad for two reasons. Firstly, sales superstars are not common. They know their worth, and if they left the company for a better offer, you better pray for another one. 

Secondly, when focus is on the sales wizards, the rest of the sales team is left in the shadows. They are not getting the coaching or mentoring they need to develop into becoming the next up and coming sales wizard. They also know their worth and if work culture is lacking – they will be gone too. And nobody wants a churn and burn culture. 

Data Science Technology Prevents Superstar Culture.

One of the biggest tech changes in recent times (that we would argue is here to stay) is the integration of data science technology into the sales process. This changes decision making entirely. Instead of making decisions based on observation and opinion. We can much more confidently make decisions based on data and numbers. We are not forced to rely on a couple sales superstars to hold things together.

Data science combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. 

By taking a data science approach we are choosing a science-driven culture.

Science-driven culture prioritizes:

1. Technology is used to make our day to day processes more efficient. It is also a crucial tool to collect the necessary data to make informed decisions.
2. Processes are what exactly your team is doing to move opportunities down the sales funnel. By prioritizing processes onus is being put on the functionality of the sales funnel steps rather than the individual. When a problem is identified, we look to how we can fix the process, not the person. 
3. Teamwork is crucial to science driven culture. All processes need to be documented and shared within the organization. When mistakes are made or insights for best practices are discovered they are not to be kept as a secret by the individual. Instead they should be shared to benefit everyone and the organization as a whole. 
4. Skills are acquired when we learn from our mistakes and successes. This is an ongoing process. When we continuously collect data and get feedback we are able to learn and improve in the places we are struggling most. 

Science-driven culture is about continuous feedback, learning and making decisions based on numbers and data. It is about fixing weak processes, not fixing people. 

Why Data Science Works

Data science relies on numbers. Not opinion. Not intuition. But cold, hard, calculable, numbers. 

Metrics must be measurable and objective. If your metrics are subjective, based on observation and personal experience – consider them an opinion. And opinions with all due respect are not important and can’t guarantee results. Without numbers and data your metrics are meaningless and left open to debate. 

Let’s apply the scientific method to the sales funnel using a subjective methodology:

1. Observation: We aren’t hitting our sales quota
2. Question: Why aren’t we hitting our sales quota?
3. Hypothesis: Hmm, well looks like the sales reps aren’t making enough calls. 
4. Prediction: If the sales reps make more calls we will make more sales. 
5. Tests: *sales reps make more calls*
6. Results: Still not hitting the sales quota.
7. Refine: Well, that didn’t work. Maybe it’s ______. (and repeat).

Using a subjective methodology (aka our intuition), we tend to make an observation, make a hypothesis, and test it.  And rinse and repeat steps 3-7 when your first hypothesis doesn’t turn out to be the problem. Repeating these steps is a massive waste of time and resources. 

However, when we use data science and recognize there is a performance gap somewhere in the funnel. The problem can be easily pinpointed by just looking at the numbers. No need to play the guessing game. From there feedback can be provided and a specific solution can be prescribed that is geared towards that exact problem in the sales funnel. This means a much faster turnaround time when solving issues. Rather than having to repeat steps 3-7 until you are just about ready to give up and try to solve the next problem.

It is beneficial at both an individual and organizational level. From an individualistic standpoint, we can analyze where a performer is successful and where they are struggling. This feedback is personalized and can help the individual to improve where they need it.

On a larger scale, this data can be used by the organization to make a more efficient sales process and provides valuable insights for the next-best action with future customers. 

Got the Data?

Most organizations, once they have reached a certain size, have a formal sales process in place and are collecting data. This ensures that they can continue to scale. A typical sales report breaks down the basic key performance indicators (KPI). Number of calls/emails, conversion rate, opportunities lost, profit margin, customer acquisition costs and so on. Not to say these are bad indicators. They are necessary for every business. The problem is they just don’t tell the whole story. 

KPI’s tend to be high level. They leave out the finer metrics that can give us a more accurate picture of what exactly is going on. It is important to know your industry and know what KPI’s are relevant to the problem you are trying to solve. Furthermore, if you are looking to take a science based approach in sales ops, it is crucial to have somebody who knows how to ask the right questions, can extract the necessary data and come up with meaningful solutions.

Tune in next week,  We’ll be following up with a post on “How to Collect Meaningful Data”

The post Data Science: The Secret to Driving Sustainable Sales and Growth appeared first on Great Ideas are Born Here.

Over the last decade we have watched Jeff Bezos climb to the top of the ladder to become the richest man on the planet. As founder and CEO of Amazon – it is clear that his leadership made an impact on the success of the multi-billion dollar corporation that started from his garage in Bellevue, Washington in 1995. 

There is one aspect of Bezos’ leadership, more specifically team building that I would like to focus on, as I believe it is one of the cornerstones of his success. It is known as the two-pizza rule. Simply put, if you cannot feed your team with two pizzas then it is too big. This number sits at a maximum of 10 highly effective team members. 

So, the secret to being a successful team is a small team. Let’s break down the benefits of keeping your team small and pizza bill low:

1. Smaller teams have healthier communication.

In a group of 10 or less, with proper introductions, team members are going to know one another by name. Which ultimately leads tighter knit relationships. Instead of seeing your teammate as employee #2342, they are another human. With their own strengths, weaknesses, fears and aspirations. Having a personal connection with team members fosters a sort of mutual respect. And creates an environment where people are not afraid to share their ideas or make mistakes.

Having a smaller team also leaves more room for open and thoughtful discussion. Team meetings can be run more efficiently with a smaller group of people. Rather than one hundred people chiming in at once. A small team meeting allows team members enough time to formulate and present their ideas in-depth. All while leaving room for feedback.

2. Smaller teams hold themselves accountable.

There is a well known theory called the “Ringelmann effect.” It was realized by French agricultural engineer Maximilien Ringelmann in 1913, it still holds true today. Ringelmann created a study where he had volunteers pull on a rope. He observed that the more people that pulled on the rope resulted in the individual putting forth less effort. 

He concluded that in a larger group, there is more anonymity among the team. It is much harder to tell who is pulling the rope and who isn’t. But in a smaller group, it becomes quite clear who isn’t pulling their fair share. 

This means, you don’t need a huge team of people to pull the rope per say. Instead you need a strong team that is going to pull their fair share of the rope, hold each other accountable and get you across that finish line. 

3. Smaller teams are nimble.

The only thing in this world that is constant is of course, change. In this fast paced world it is crucial that teams are agile and can respond to changes both quickly and efficiently. In a large team, decision making is often a long, drawn out and bureaucratic process. A slow response to external changes can result in a variety of losses for an organization. And in some cases organizations will end up folding – unable to keep up. 

On the other hand, a small, tight knit team can quickly come up with strategic responses to changes in their market and environment. With fewer decision makers, the decision making process is dramatically reduced and strategy can be implemented at a much faster rate. 

4. Smaller teams cost less money.

This almost goes without saying. Of course, having ten team members is going to cost less than fifty team members. Less people equals less resources spent. Yes, this even applies when you have some real unicorns on your team that might cost a little (or a lot) more than your average employee. 

On that note, it is worth investing more in a small team that is multifaceted and offers deep expertise in a variety of areas. 

5. Smaller teams are more innovative.

When seats on the team are limited, you have to be picker with who makes the cut. Having a small, focused team, full of multifaceted experts (in a variety of fields) can make it much easier to come up with creative solutions to some of the most pressing challenges businesses face today. Take a look back in history, some of the most notable inventors did not just specialize in one narrow discipline, rather they had a wide range of skills. 

Lets use Benjamin Franklin as an example. He wore many hats. He was one of the founding fathers of the United States, a writer, a scientist (that most notable made many major contributions towards electricity research), a businessman, an author and printer, and made many civic contributions to his community, by founding a fire hall, academy, hospital, and an insurance company. This paragraph hardly does any justice for the guy. But my point is, finding a few people with deep skills and curiosity will drive innovation at a much faster rate than one hundred average joes would.

One example that comes to mind when considering team size is a 2015 interview between Ried Hoffman, host of Masters of Scale, and Eric Schmidt, former CEO of Google. Schmidt recalls his introduction to the Google founders team and their strategy to oversee growth within the company. 

In one year, Google had quadrupled their number of employees. Eric observes that exponential growth is not always a positive attribute. Rather, the team size should be scalable to the product or service being offered. Growth should be controlled and bringing on new team members should be strategic. 

To control growth, Eric Schmidt did a full review on hiring and the hiring process. Each employee would have something to offer and was brought on to contribute to projects in a specific way. This would reduce the number of what he referred to as “glue people.” Employees that were loyal and assisted in activities but were not necessary to the teams success.

The benefits to having a small team are clear, but what does it actually take to make your small team run smoothly, efficiently and meet deadlines? Here are three tips on building a small team for success.

• Hire wisely. Just because your team is smaller than ten, does not automatically make it an all-star team. It is important to choose your teammates carefully when there are limited seats available. You want to choose people that offer an array of skills, with a deep understanding of both the business and technical side of things. 

• Create a thriving work culture and environment. This is important to establish early on when creating your team. Team culture is created whether intended or not. And who you bring onto the team will help define the culture. Building strong relationships among team members in the early stages creates a space that team members can be open and vulnerable with one another. A space that it is okay to brainstorm and make mistakes will lead to innovative solutions faster. 

• Outsource projects. No matter how fantastic your team of ten really is, you won’t be able to take on the entire world. Recognize when something that is out of your team’s scope or that a group of experts might be able to do better. Then hire the right consultants to take care of it. Firstly, this ensures that the job is going to get done right the first time. Secondly, this prevents your team from becoming overwhelmed by work load. Instead they can focus their attention towards challenges that they are skilled to fix. 

This is not to say that there is no place for large teams, but a business must carefully evaluate the scale and resources available when choosing the right size team for the project. Larger teams tend to work best when looking to maintain or advance and develop in their given industry. Whereas smaller teams are best in situations where innovators are trying to keep up with the latest trends or looking to disrupt the status quo – which is what most of us start-ups would like to do, isn’t it?

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“We are drowning in information and starving for knowledge.” — John Naisbitt.

The Era of Big Data

We have entered the era of big data. For example, there are about 60 trillion web pages; 300 hours of video are uploaded to YouTube every minute, amounting to 10 years of content every day; the genomes of 10000s of people, each of which has a length of 3.8 × 109 base pairs, have been sequenced by various labs; Walmart handles more than 1M transactions per hour and has databases containing more than 2.5 petabytes (2.5 × 1015) of information [1]; We are currently creating around five exabytes a day roughly equivalent to 500 million songs — the amount of data available today is giving machines the possibility to become super-intelligent.

What is ML?

This deluge of data calls for automated methods of data analysis, which is what machine learning provides. In particular, machine learning (ML) is defined as a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data) [2]. A more technical definition of ML is “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation” [3].

AI vs ML?

It’s worth noticing that often ML is used with artificial intelligence interchangeably. Although artificial intelligence is technically broader than ML and they are different, for the purpose of this note, we treat them the same.

Why Now?

Now, you might ask, how old is this stuff and why is it getting a lot of attention now? Artificial intelligence was founded as an academic discipline in 1956. It because most of ML methods work well when you have a large amount of data (to be precise it really depends on the problem you are trying to solve) and as noted we have entered into an era that there is no shortage of data, yay! Another interesting thing recently happed; our computers got way stronger and faster than before. Analyzing and extracting information from an enormous amount of data is not trivial. It needs a lot of computational power and the introduction of graphics processing units (GPUs), which were developed to speed up the graphics in our everyday computers and especially in the gaming world, to ML world changed the game.

What are Some of the Applications of ML?

What are some of the applications of AI/ML? Good question. Although you might not notice it, ML already is a big part of our lives. Amazon makes its recommendations based on a set of ML algorithms called “Recommender systems” specifically a hybrid of “Collaborative filtering” and “Content-based filtering”. Google uses ML to detect spam emails. Facebook uses ML to show you the content that you would find interesting. Tesla is using AI/ML to make self-driving cars. Intelligence services are using ML to detect criminals in crowds and …

ML and AI are already here. The question is how to align your business to benefit from it rather than getting killed by it.

1. “Cukier K., The Economist, Data, data everywhere: A special report on managing information, 2010, February 25, Retrieved from http://www.economist. com/node/15557443”
2. “Kevin P. Murphy , Machine Learning: A Probabilistic Perspective Hardcover — Aug 24 2012”
3. “Kaplan, A. and M. Haenlein (2019) Siri, Siri in my Hand, who’s the Fairest in the Land? On the Interpretations, Illustrations and Implications of Artificial Intelligence, Business Horizons, 62(1)”.

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Amid a global pandemic, economic evolution, technology progression and life transformation there is no surprise many people are concerned with ‘The Burnout’.

 Study shows that when people are more content with their work, they are more likely to produce better results. integrityCo is well aware of the stress of modern economic demand. While everyone is focused on hustle and productivity, our company promotes a holistic life/work balance.

Working in a company that promotes these values was music to my ears. In addition to being a marketing junkie, I am also a yoga teacher and I make sure that my team stays positive and content. (So while everyone is busy with content marketing, we focus on marketing and life contentment!)

Hi, my name is Kim Bassan and I’m a marketing intern at IntegrityCo. While I was trying to brainstorm trends on artificial intelligence and machine learning I came to the conclusion that our society is facing extreme challenges beyond the computer.

In times where we spend most of our days in front of a screen, touch of humanity and empathy could be a nice break. Today, I will share with you a glimpse of my interests and share my 5 tops tips to finding work/life balance and avoid the burnout.

1. Take breaks

Your brain needs to rest! It is essential and necessary. Yes, there is pressure to meet quotas and deadlines but your brain demands rest as well. Thinking and focusing for a long period requires energy, and taking a break will keep you focused, allow you to think logically and in return progress towards your goal faster and with a clearer mind. So, if you are one of these people who thinks that taking a break will put you even further behind, think again! (but then take a break)

For fast-acting relief, try slowing down.

―Lily Tomlin

2. Get into your body

And I’m saying that not as a biased yoga teacher, rather as a sedentary worker who spends most of the time on the computer. The human species was designed to move, walk and activate our muscles. Slouching at your desk can damage your spine, shoulders, lower back and generally hurt your posture which may extend to your emotional health. 

So, while you’re reading this blog, stand up, shake your legs, give yourself a nice round of shoulders. Drop-in with your body, I promise a physical break can go a long way! 

3. Allow yourself to have those ‘blah blah’ conversations

I know we all avoid those casual talks because we think they might be useless. Now that most of us work remotely, we don’t get the opportunity to socialize very much. Don’t cringe at the small talk, ask your coworkers questions and allow yourself to drift off work topics from time to time. It is refreshing and you may surprisingly find a common interest with one of your colleagues! 

4. Diversity and creativity

You might be thinking “Kim, I can barely draw a stick figure, you ask me to be creative?!” And I’m here to answer: 

“Yes, you can teach yourself to be creative!”

Stay inspired by diversifying your resources, start getting ideas from other fields and translating these practices into your work environment. Creativity is not about being Leonardo da Vinci it’s about pushing past the boundaries, letting your mind wander for a few minutes and never, ever doubting yourself. 

For example, I was thinking about what to write for my blog post. I was thinking about writing all kinds of marketing practices which are probably educational and valuable. But, there are so many blogs about SEO, email marketing and many more that I decided to take a different approach and be creative! Bridging between my yoga knowledge and the marketing work world to bring something relevant just as A.I and machine learning are.

If you want to succeed, you have to fuel yourself. You cannot pour from an empty cup. ― My Mantra

5. Take care of yourself in your off-hours- set the boundary

In a time where personal and workspace boundaries become blurred, it is important to distinguish between work time and home time. 

While working from home means more flexibility, no commuting and other benefits, it faces us with big challenges as well.

Procrastination, productivity, lack of team collaboration and most importantly, where and when do we draw the line between work and home hours?

To create this distinction make sure to communicate your needs with your surroundings.

• Block time:  set a schedule and stick to it. Make sure to set aside some time for your family as well. 
• Set the space: shut the door, organize your desktop, whatever works for just make sure there is a physical separation between leisure and work time
• When the clock hits- you’re done: don’t be tempted to check emails, Slack your team, just stop and dedicate some time for your family, significant other and yourself. 

You need time to sleep, eat, exercise and leisure. Rejuvenate and fuel your system with your loved ones, work will be there tomorrow and every day. Make sure you invest in yourself, it will help you come back stronger and motivated. 

Don’t confuse having a career with having a life.

―Hillary Clinton

While it is nice to wear my yoga pants for work, remote work faces us with new and different challenges. In our hustle-bustle culture economy, we need to actively engage with practices that encourage us to put ourselves on our ‘to-do” list as well. Just as Hilary Clinton said, making a living doesn’t mean you’re fully living! 

Find your tricks and rituals that help you stay away from the BURNOUT zone

Comment below which one of the practices in this blog you liked, and let me know what is your strategy to get work life balance! 

Stay tuned for this part 2 series in which I will provide tangible practices such as breathing and mindfulness techniques that you could try to use while achieving work and life balance.

The post Top 5 tips to avoid burnout and maximize productivity appeared first on Great Ideas are Born Here.

We will spare you the worn-out talking points, we all understand that COVID-19 has forever changed our familiar life and economy. Face masks, two feet distance and all of a sudden we became hand-sanitizer experts. But to stay successful in the market, the real expertise you want to acquire for remote working conditions is how to manage your business successfully.

While COVID-19 faces us with many challenges, technology has also progressed and offers creative ways to work from home and manage a team, clients and lots of data.

So, with social distance standing in our way, how do we maintain work collaboration, customers, leads and all of our information in this digital world?

By no means is this new technology, most companies are using a CRM of some sort. And with a consumer-driven economy, all companies can benefit from this tool. From E-mail marketing, sales, business development, customer service, B2B, CRM is your company’s go-to for online productivity.

But what is it and how can we use it to our advantage?

CRM is the acronym for customer relationship management and just as its name suggests, it is a software that helps businesses to manage relationships with customers, team and information. It is the substitution of the physical space we used to hold and translated it to the virtual world for the organization’s workflow.

With remote-working and new business models, having a successful system to operate within is essential to your success. However, most sales reps are not using it to its full capacity. 87% of sales reps admitted they only use the CRM because their company requires them to and 78% said they only “check the boxes.” This means a lot of important activities and information are being left out of the CRM and kept in the sales rep’s records. Which of course will have dire consequences for the business. When this much information is being left out of your main database it is a given that business will fall through the cracks and relationships will fall off. Amid a recession triggered by COVID-19, we must adopt new digital techniques to keep our business in the game.

In this article, we want to show you how you can leverage your CRM to make remote work more efficient for you and your team. Your team must understand that CRM is not just a tool for management to police what everyone is doing. Instead, it is a sales enablement and communication tool that can be used from anywhere. If it isn’t already, this should be your business’ new home base. So be sure to get your sales team on board with using the CRM.

Enter all relevant data and activity into your CRM.

This is the most crucial step a sales rep could take to improve the business while working from home. Your CRM is a secure and centralized database. Having all your data in one place has an array of benefits.

Keeping detailed records means that anyone on the sales team can quickly pull up a customer’s history and offer top-notch customer service because they already know what preferences they might have or challenges they might be facing. All of a sudden extra data comes into play! Our computers can hold more information than our brain and with an organized CRM you can pull that bit of information at the right time, the right place and SEAL THE DEAL!

And for the future, having heaps of relevant data is valuable. Data can be analyzed and leveraged in many ways to make a customer’s experience more personalized, improve customer service and increase revenue.

So all in all, with data being romanticized in the modern world, a bit of extra data can never hurt anybody…

Integrate all workflow applications into your CRM.

Integrate emails, calendars or any other workflow applications your team might be using. Keeping all your information on one platform reduces confusion and ensures that tasks or meetings don’t fall through the cracks (which can happen with distractions around the house).

It is the easiest way to communicate, create a smooth operating system across multiple channels and automate any task that doesn’t need direct human interaction.

All in all, it saves you a lot of time, energy and consequently, money.

Clean up your CRM data and automate where you can.

We cannot emphasize this enough. Seriously, a CRM filled with junk either turns a sales rep to use their methods of maintaining records or they end up wasting an unnecessary amount of time trying to sort it out. During this time, many people holding off on investing in their companies, you might find yourself with more downtime than usual. It is the perfect opportunity to start tidying up your CRM. You can start by getting rid of any redundant or useless fields, filling in any missing information or activity on prospects and customers, update leads that have fallen through the cracks, and merge duplicates.

Of course, if your CRM is large it could take years to clean it up. If duplicate and outdated leads are a challenge, now is the time to look into getting some of these mundane and time-consuming tasks automated. It will save you a lot of technology frustration, ultimately, creating more time to focus on developing your business, building stronger relationships and reaching a new level of success.

Final words.

While there are many CRM options in the market, each one specializes in different challenges. Pick the CRM that tailors to your goals and business strategy. By using CRM you connect all your workpieces and letting the CRM bring your business to new success.

You can think of your CRM as the new office. With employees working remotely, this is the new home base where everyone on the team can coordinate and keep up to date on what needs to get done. While some of us are still trying to navigate through Skype, Facetime, Slack, Zoom, Google Hangouts and making our home as our office. The CRM was built for the remote worker, collecting, storing and analyzing your data. So, it increases work efficiency and now is the time to leverage your CRM!

The post The Rise of the CRM in a Work from Home World appeared first on Great Ideas are Born Here.

Hamid has been in the tech space for over a decade, as a software engineer, data scientist, entrepreneur and consultant. He has always been passionate about using technology, more specifically AI, machine learning, and data science to make business processes simpler and more efficient. 

Throughout his time in the tech space and as an entrepreneur he noticed some recurring patterns that disproportionately affected small and medium sized businesses (SMBs), that just didn’t quite sit right with him…

The first thing he noticed was that many startups, small and medium sized companies did not have the capacity to come up with innovative technological solutions to their everyday business challenges. Oftentimes, this comes down to an affordability issue. As a new company there is not always an excess of capital available. And to bring a team of “experts” in is a huge upfront investment, and most smaller companies just don’t have the budget for.

In other cases, there is already a team of data scientists but they lack experience, knowledge and aren’t sure how to ask the right questions and identify which projects to invest in for the highest ROI. A successful project not only requires a talented technical team but experienced product and project managers that understand the business behind it as well. If you’re lucky you come across that unicorn 10X data scientist that both understands the business side and the  technical side of the projects. Unicorns are damn expensive to hire full time and typically don’t work for a salary. 

The second thing he noticed was that companies that did have the fiscal capacity, who approached consulting firms felt that there was a mis-alignment of interests. Rather than being provided with solutions to solve their business challenges, they were offered strategies with limited guidance on execution… which in most cases does not work. Typically, firms that offer both strategy and execution are pretty good at what they do, but are exorbitantly expensive and unaffordable for the bulk of SMBs. This results in clients spending a ton of their budget on a project that has an absurdly low ROI. With much needed company resources essentially being burned right in front of their eyes. 

With limited access to affordable and innovative technological solutions, small and medium sized businesses don’t have much of a fighting chance at competing within their market. This even includes large low-tech companies in manufacturing, transportation, etc… While tech-positive corporations invest in more and more advanced technology to improve operations and efficiency, they gain a massive advantage in their market. The continuation of tech development and expansion without a disruption for these large, tech savvy corporations, means that smaller businesses are getting strangled out of the market. 

2020, undisputedly has been a year for the books. The misfortune that many of us have experienced or witnessed this year, have brought to light many serious social and economic problems that our society faces as a whole. 2020 has left many of us questioning our own morals, judgement, re-evaluating where our priorities now stand and even where we are spending our hard earned dollars. 

This was certainly true for Hamid, using his own experience and knowledge, he felt the best way he could chisel away at these problems was through entrepreneurship. He wanted to create something that would disrupt the patterns he noticed in the tech space. Furthermore, something that would emulate his own core values; innovation, humility, quality, and most importantly, integrity.

And, long behold the creation of integrityCo. AI & Business experts, who unlock the opportunities in your data and excel your business. With low risk and high reward.
Enabling companies to grow, advance and bring your vision into reality.

The first mission of integrityCo is transparency from start to finish. While integrityCo loves to take on a great challenge, there is also an urgent sense of accountability. A free consultation will tell whether or not a project is worth investing in – integrityCo only commits itself to projects which they believe has an ROI of at least 10X, because an investment to improve business operations shouldn’t be like playing a game of roulette. 

The second mission of integrityCo is accessibility. Making advanced technology more accessible to all companies regardless of size. SMBs have been hit the hardest in 2020. According to Business Wire, 43% surveyed reporting a significant to severe impact as a result of COVID-19, while CEO’s of massive corporations like Amazon, Microsoft and Zoom saw their wealth increase by as much as $48 billion. While SMB’s would greatly benefit from business process optimization, with a lack of financial resources it is not always possible to make these kinds of investments upfront – even if it would pay off in the long run.

The third mission is to promote equality, diversity and accessibility within integrityCo. At some point in our lives we have all heard somebody say “change starts from within.” While this statement might be overused and a little bit corny, there is some truth to it. integrityCo’s team is highly inclusive and made up of people of colour, women, all coming from varying degrees of education and life experience. integrityCo puts emphasis on a workspace that is inclusive, experimental and safe to be vulnerable. This trifecta has created a forward thinking team, who is not afraid to think outside the box when solving some of the most pressing challenges that businesses face today. 

As a start-up business, integrityCo has put emphasis on working with other start-ups, small and medium sized businesses. Ensuring access to top technology that is affordable, innovative, data-driven and tailored to the individual needs of each business. And most importantly provides solutions. All while building more meaningful relationships, partnerships and a stronger community of people and businesses with similar mindsets. 

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Hamid Omid is the founder of integrityCo, with years of experience in the field of data science, machine learning, product management and a great sense of humour, Hamid enjoys helping companies identify valuable and transformative opportunities with a focus on digital products and big data. As the industry begins to understand the unexploited resourcefulness of novel technologies such as AI , executives are looking for strategies to innovate and create value from their data. Hamid shares his expertise to help companies plan successful AI & ML products and reach their fullest potential for success.

We interfere with artificial intelligence (AI) and machine learning (ML) as part of our daily life. From movie recommendations on Netflix, advertisement targeting on YouTube, biometric facial recognition to much more. AI and ML accumulate a lot of ‘buzz’ and creates excitement but how do you choose the right project? The one that will succeed and generate increased revenue for your company

In 2017, firms around the world spent over $21.8 billion on mergers and acquisitions related to AI. We are at the beginning of a revolution, as McKinsey predicts that digital innovations will provide an estimated economic impact of about $370 billion per year worldwide by 2025. However, despite the glamour excitement around AI, we must also not be blinded and pick cautiously your next AI project. Despite the positive association, the industry cultivates around this technology. According to Harvard Business Review (HBR), more businesses buy the promise of Big Data and AI initiatives, in fact, they found growth of 65% from last year. However, Forbes recently reported that many executives worldwide have not seen value from AI investments. So with technology promises, some billion-dollar projects are failing to deliver on their promises, and we don’t want yours to be one of them. 

We brought you Hamid, an AI and Data expert to give you 4 tips to choose the right AI project and avoid the pitfalls of another risk that will leave you with nothing but empty promises and money loss.

At integrityCo, our team has over 60 years of collective experience with machine learning, big data, data science, and software development — so when it comes to AI projects, we’ve seen everything. Our mission is to help you to make the most of the data you already have. And as technology grows and we hear about big data everywhere, companies rush to invest their money for growth, we thought it would be helpful to share 4 common pitfalls and their solutions when choosing your next AI project. After you’ll read this article you will be able to choose your next AI project wisely and ensure success. 

As social human beings, our success relies on our collaboration with our environment and that’s why our first tip is about teamwork!

1. Team misalignment

All projects, especially ones that move towards human innovation, depend on team collaboration. Misalignment among stakeholders is like fighting an uphill battle.

According to an HBR survey, 93% of respondents claimed that team disagreements and issues in the process of the project were the number one cause of the failure of their projects. With a high turnover economy, the challenges with culture change have been dramatically underestimated. HBR found that 40.3% identify a lack of group organization, and 24% cite cultural resistance as the primary factors stifling business adoption which disrupts the workflow. Consequently, negatively impacting the return of investment for AI projects.

Solution: Communication is key

With the difficulties of working remotely, communication is still the key to success. work can flow smoothly once all the working brains agree on the project strategy. Diverse perspectives are valuable for the team to grow and evolve. Therefore, allowing everyone to voice their opinion is critical to the project’s success. We recommend beginning your project with a workshop. By facilitating an engaging brainstorming session, people not only feel comfortable sharing their thoughts, but it also gets stakeholder buy-in, creates alignment, and gets everyone on the same page which saves time in the long run.

2. Quantity over quality

Data is critical to making informed decisions on AI projects. Often in the interest of saving time, many companies approach data gathering with the mindset that more is better. Unfortunately, this results in teams feeling overwhelmed and unsure of how to parse through hundreds (sometimes thousands) of datasets to determine what is useful. In conducting data analysis for clients, we have come across terabytes that provided little insight into their problem and megabytes that were so rich with information we could build a sophisticated ML project. The key is to ask the right questions when trying to implement an AI or an ML project. That’s exactly what integrityCo focused on. Finding the root of gold mine data. 

Solution: Take small steps, and when in doubt, outsource

Little by little, little becomes a lot. To determine relevant data, start with a small and easy exploratory analysis. Use what is readily available to determine if you can pull out any signals. An experienced data scientist should carefully take step by step to identify patterns. If nothing comes out from one path, try a different mindful strategy. Instead of trying to do everything at once, try to do one thing in order to get everything. Be ready to detour, start over and keep being alert to any signal that may emerge along the way. 

Developing an AI product is resource-intensive, and for many organizations, it’s challenging to allocate the in-house time and talent to work on every facet. Hiring a consultant with relevant domain and data science experience can be a great investment to ensure you collect quality data PLUS get an external point of view. One that your internal team might have not been aware of or qualified for.

3. Irrelevant KPI + small impact

We’ve seen clients get swept up in fun and interesting projects only to find out the business value is centered around vanity metrics. For example, clients measure an increase in visitors when their focus should be increasing ARPR [Average revenue per referral]. So, before you start pulling your big guns in any project, identify your goals, opportunities and measure of success. Even if a project is tied to a relevant KPI, the effort required to make an impact may not worth the stakes. Passion projects are important, but before taking one on, first, determine relevant KPIs and what would you consider as a goal attained.

Solution: Know your business

To determine relevant KPIs, you need to know your business — this may sound trivial, but many companies can’t articulate the problem they are solving. You want to be able to explain it clearly, fast and so that anyone can understand, guide yourself through this thought process:

• What are we trying to solve?
• For what purpose?
• And what impact does it have on our business? Community?

As you are going through this exercise, think of ROI, not COI (coolness of investment!).

Simplified Business Model of an Affiliate Marketplace

A tip for calculating ROI: ROI can be determined by looking at how much you stand to make or save if the project succeeds. The example below demonstrates how you might go about forecasting ROI for a potential affiliate marketplace project.

Simplified Math Equation of an Affiliate Marketplace

4. Unrealistic goal

Consumer-facing businesses want to make a chatbot that reduces staffing costs. E-commerce shops would like to anticipate what their visitors are going to buy and target accordingly. Pharmaceutical companies would love to make a drug for cancer.

We get it, everyone wants to be the next leader, we live in a very competitive based market but, if your goal is not realistic, it will simply be impossible to attain and your project will fail. So, check-in with reality and acknowledge your work scope. After years of executing data science projects, we’ve noticed a trend. The chance of success appears to be related to the complexity of the problem. The more complex, the less likely it is to succeed.

The more complex, the higher chance of failure!

Solution: Simple is better

Partnering with a consultant or an agency that understands how to make the complex simple is a great way to increase success. And POWERSHiFTER is the expert here. As big believers (and practitioners) in simplifying digital experiences, they can attest to the importance of choosing simple projects. “What I’ve seen time and time again is that the right idea is always the simplest,” said JP Holeka, CEO & Founder of POWERSHiFTER. If your company’s BHAG (Big Hairy Audacious Goal) is to create a chatbot that reduces staffing costs, break it down into smaller steps.

Thriving in uncharted waters

AI and ML are being positioned as the next great step forward for humanity — but we have a ways to go before society realizes the full benefit of these powerful technologies. Technology is dynamic and constantly shifting. Every day we develop, learn, reveal a new idea. Companies looking to dive into AI and ML projects are navigating uncharted waters and for this reason, you need the sharpest, experienced but also open-minded minds. If your organization doesn’t have the in-house expertise, time, resources, or methodical R&D process, we encourage you to hire outside consultants early on to get going in the right direction. All projects come with a risk of failure, but with the right team, knowledge, KPI and strategies… you will see yourself on the path towards success.

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The current coronavirus pandemic situation has created a sudden change in our everyday lives that was unforeseen just a few months ago. As individuals adjust to the “new normal,” businesses should also take a moment to reassess their situation.

Suddenly, the market is upside down, your team is working remotely, and a good portion of your team probably doesn’t have as much on their plate. Although the market is showing signs of coming back, it might take many months to a few years. This uncertainty presents an opportunity to concentrate on the “fundamental” work that’s always in the “to do” bracket. Tasks that were a lower priority with everyone focused on the daily business operations is now perfect for getting done. It’s time to position your company to leverage the current situation so that your company is super competitive in the “new normal.” Well, let me try to explain:

Utilization = morale

We know that excellent staff morale is key to productivity and utilization. I would argue that those who are most engaged are those that understand the reasons for what they are doing. If they are aligned with the company’s vision and understand their roles and possible impact, they will not need your constant motivation. Nothing creates a downward spiral more than underutilization of staff already suffering from the “Mushroom Syndrome.” Now is the perfect time to create alignment and focus. Typically, teams are too busy when things are going well

I’m guilty of this; you’re guilty of this. Typically, when things are healthy, and the company is doing well, everyone is laser-focused on their commitments and targets. We are guilty of working ‘in the business’ rather than ‘on the business.’

The market has changed, and the world is a different place–get ready for it

Some of the effects of COVID-19 are with us for a long time, and some are likely permanent. Now is the time to get ready for dynamic changes that are new to everyone. Markets after the 2009 crash were different. Similarly, the markets after September 11 also changed. The changes after the two events were different too! What do you need to be ready? Data can tell you a lot about this. It would help if you readjusted some of those fundamental assumptions which worked previously. Do you know which ones they are?

New technology initiatives take time

You have got your teams focused on the next 12 months of work; now you need to start thinking of the future. Once you have set the company’s direction, you need to gather intelligence to determine the criteria for success and failure. To quickly identify where the market is headed and stay on the leading edge. The best way of creating a picture is by analyzing many data. That’s where technology can help identify new trends and emerging patterns, but the intelligence lies in understanding data. Implementing technologies like AI and ML takes time. More than that, gathering data takes even longer, and it requires a lot of trials and error testing. Experiment with it while your business is not at full capacity. Now is the best time for when the market comes back, you won’t have the time.

So what?

OK, you’re convinced that it is a good time to do some fundamental work. Where to start? Start from where the impact is. Try to avoid shiny objects and only do what matters. I’m going to write about this topic next week so please stay tuned! Before that let’s look at some other bullet points.

Measure twice and cut once

You’ve heard the saying “Measure twice and cut once,” well, this also applies to businesses. By that, I mean companies should spend time planning their mid to long-term course before committing the workforce to a particular path. Moreover, that same workforce should be part of the planning process, so they have a stake in the outcome.

During this downtime, it’s your job, as the boss, to create the company vision for the 10–5–1 year horizons. You are responsible for the big picture. Where do you see the company (in terms of revenue, size, product development, market capture, and any other target you have been dreaming about) in 12 months from now, then 5 years, and finally 10 years from now. Identify the targets as accurately as you can and see if your staff think it’s possible. If they like what they see, they’ll provide most of the solutions to achieving the ‘want.’

Try filling in the details of your targets in the following table style:

Does everyone working for you know what the company does? Why it exists? You may think those questions are trivial, but to get alignment across the board, everyone must understand what service(s) the company provides, and why it exists. Now is your chance to consider how the current Covid-19 climate can be an opportunity to beat the competition.

In the following diagram, I created a mind map to identify the business of a company. It needs to be simple enough for anyone to understand.

What YOUR landscape looks like?

Start by identifying your current place in the market and then define how new opportunities are becoming apparent. Let your staff tell you what they think.

Along those lines, I created the following drawing for a company to highlight its position in the market. It shows their competitors, suppliers, partners, customers, and other channels. Again, a mind map is the easiest way for everyone to follow:

More efficient and last longer

Use your best and brightest employees to help set the path forward. Once they fully understand what the company does, why it exists, and where it needs to go, they’re motivated to succeed.

Task your leaders with creating milestones to achieve the goals for the next 12 months, let them demonstrate their preparedness to meet those targets. When that occurs, your job is to shepherd them, provide the resources, and trust them.

Finally, it’s very important to find us on LinkedIn and let us know what you think! Always happy to connect.

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