YES! Data is extremely important for your business.

A human body has five sensory organs, and each one transmits and receives information from every interaction every second. Today, scientists can determine how much information a human brain receives, and guess what! Humans receive 10 million bits of information in one second. Similar to a computer when it downloads a document from the web over a fast internet connection.

But, did you know that only 30 bits per second can be processed by our brains. So, it's more EXFORMATION (information wasted) than information gained.

Data is everywhere!

Humanity surpassed a zettabyte in 2010. (One zettabyte = 1000000000000000000000 bytes. That's 21 zeroes if you're counting!)

Humans tend to generate a lot of data each day - from heart rates to favorite songs, fitness goals and movie preferences, you find data in each drawer of businesses.

Data is no longer restricted to just technological companies. Businesses as diverse as life-insurance agencies, hotels, and product management companies are now using data to improve their marketing strategies, customer experience, and to understand business trends or just collect insights on user data.

Increasing amounts of data in the rapidly expanding technological world of today makes the analysis of it much more exciting. The insights gathered from user data are now a major tool for decision-makers. I've also heard that these days data is used to measure employee success! Wouldn't appraisals be a lot easier now? :P

Forbes says there are 2.5 quintillion bytes of data created each day - and only 0.5% data of what is being generated is analysed! Now, that is one mind-boggling statistic.

So, why exactly are we talking about data and its inclusion in your business? What are the factors that encourage data dependency? Here, I have listed 6 solid reasons as to why is data so important for your business - you'll thank this article later.

Aspects of Data Analysis and Visualization

What do we visualize? Data? Sure. But there's more to data.

1. Variability: Illustrates how things differ, and by how much
2. Uncertainty: Good visualization practices frame uncertainty that arises from variation in data
3. Context: Meaningful context helps us frame uncertainty against underlying variation in data

These three key aspects create questions that we seek answer to in our business. Our attempts at data analysis and visualization should focus on marginalizing the above three points to satisfy our quest of finding answers.

1. Mapping your company's performance

With tens of data visualization tools like Tableau, Plotly, Fusion Charts, Google Charts and others (my Business Data Visualization professor loves Tableau tho! :P) we now have an access to ocean of opportunities to explore the data.

When we focus on creating performance maps, our primary goal is to provide a meaningful learning experience to produce real and lasting business results. Performance mapping is also essentially important to drive our decisions when selecting strategies.

Now let's fit data in this whole picture. The data for performance mapping would include the records of your employees, their job duties, employee performance goals with measurable outcomes, company goals and the quarter results. Do we have that in your business? Yes? Data is for you!

Implement all these data on a data visualization tool and you can now map if your company is meeting the expected goals and your employees are assigned the right mission. Visualize your economy for a desired time frame and deduce all that is important to you.

2. Improving your brand's customer experience

It will take only a few unhappy customers to damage or even disrupt the reputation of the brand that you have earnestly created. The one thing that could have taken your organization to new heights-Customer Experience is failing. What to do next?

First things first: unearth your customer database on the basis of behavioral business. Plot the choices, concerns, sticking points, trends, etc. across various consumer journey touchpoints to determine points of improvement for good experiences.

PayPal Co-Founder Max Levchin said, “The world is now awash in data and we can see consumers in a lot clearer ways.” The behavior of customers is a lot more visible now than ever. I say, leverage that opportunity to create a pitch perfect product strategy to improve your customer experience now that you realize your users.

Businesses can harness data to:

1. Find new customers
2. Track social media interaction with the brand
3. Improve customer retention rate
4. Capture customer inclinations and market trends
5. Predict sales trends
6. Improve brand experience

3. Make decisions quicker, and solve problems faster!

If your business has a website, a social media presence or involves making payments, you are generating data! Lots of it. And all of that data is filled with immense insights about your company's potential and how to improve your business

There are many questions we in business seek answers to.

1. What should be our next marketing strategy?
2. When should we launch the new product?
3. Is it a right time for a clearance sale?
4. Should we rely on the weather to see what's happening to business in the stores?
5. What you see or read in the news would affect the business?

Some of these questions might already intrigue you by the idea of getting answers to from data. At different points, data insights can be extremely helpful when making decisions. But how wise is it to make decisions backed by numbers and information about company performance? This is a sure-shot, hard hitting, profit-increasing power you can’t afford to miss.

4. Measuring success of your company and employees

Most of the successful business leaders and frontmen have always relied on some type or form of data to help them make quick, wise decisions.

To elaborate on how to measure success of your company and employees from data, let us consider an example. Let’s say you have a sales and marketing representative that is believed to be a top performer and having the most leads. However, upon checking your company data, you come to know that the rep closes deals at a lower rate than one of your other employees who receives fewer leads but closes deals at a higher percentage. Without knowing this information, you would continue to send more leads to the lower performing sales rep and lose more money from unclosed deals.

So now, from data you know who is a better performing employee and what works for your company. Data gives you clarity so you can achieve better results. By looking at more numbers, you pour more insights.

5. Understanding your users, market and the competition

Data and analytics can help a business predict consumer behavior, improve decision-making, market trends and determine the ROI of its marketing efforts. Sure. The clearer you see your consumers, the easier it is to reach them.

I really loved the idea of Measure, Analyze and Manage introduced in this WordStream article. When analysing data for your business to understand your users, your market reach and the competition, it is essentially important to be relevant.

On what factors and for what information do you analyse data?

1. Product Design: Keywords can reveal exactly what features or solutions your customers are looking for.
2. Customer Surveys: By examining keyword frequency data you can infer the relative priorities of competing interests.
3. Industry Trends: By monitoring the relative change in keyword frequencies you can identify and predict trends in customer behavior.
4. Customer Support: Understand where customers are struggling the most and how support resources should be deployed.

In the rapidly expanding technological world of today, using data to help run your business is the new standard. If you’re not using data to guide your business into the future, you are sure to become a business of the past!

Fortunately, the advances in data analyzing and visualization make growing your business with data easier to do. To analyse your data and get the insights you need to propel your company into the future with data.

Know Your Author

Rashi is a graduate student and a UX Analyst and Consultant, a Business Developer, a Tech Speaker, and a Blogger! She aspires to form an organization connecting the Women in Business with an ocean of resources to be fearless and passionate for the work and the world. Feel free to drop her a message here!

Not better, not worse… just different

“React.js is so much better than Angular”. “Java sucks, no one uses it anymore… we should use Golang”. “Pineapple is the worst pizza topping”. You’ve probably heard one of these very straight opinions. One option is the best, the other is the worst, X is better than Y and so on. But Java is still one of the most popular languages in the world. Angular gives a decent fight to React.js. Pizza with pineapple… well, that’s Ewwww.

Does that mean that more than half of the people are clueless? Or don’t know how to tell which technology is better or make the right choices? Maybe we should stop using terms like “better”, “worse”, “best” and shallow comparisons when evaluating alternatives. Instead, we should focus on the benefits of each solution, the disadvantages, and which one is a better fit for our specific problem.

Evaluating alternatives

One way to do this is by creating an alternatives comparison table:

• Write the different alternatives in the header. Use each column to evaluate one alternative. Pick 2–5 alternatives.
• Write the different properties that you think are important for evaluating the different alternatives. Pick 2–5 most important comparison properties.
• Keep the last row for summing up. There is no better/worse solution, focus on why each alternative solves the problem.

“What would you have to believe to choose this approach?”

For example, let’s assume that we have a problem that can be solved in two ways. One is S.O.L.I.D and the other one is hackier. Some might say that we should always use a S.O.L.I.D solution, regardless of the circumstances. Does that mean that anyone who uses hacky code is a bad developer? I doubt it.

Let’s put the alternatives in a table:

After composing this table, we can focus on the bottom line, and tie it directly to our goal.

An example of cases for “shipping as fast as possible, and we are ok with compromising on future quality” could be:

• A severe bug that exists in the system. Every day that passes without a solution can cause long-term damage.
• We have a contract with a customer to ship the solution on a specific date. If we miss the deadline, there may be legal consequences.
• The company has cash flow issues. Shipping the solution early can have a huge impact on our business stability.

As you can see, using S.O.L.I.D is not always the better approach. If we care about code quality, we should definitely default to it, but we must make sure that we know the tradeoffs. Choose one solution over the other because you believe this is the best path to reach your goals. Don’t do it just because Uncle Bob or someone in your company said it’s better.

Don’t do reviews only to get the “stamp”

_Photo by [Unsplash](https://unsplash.com/photos/hgITU7cj7k8?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText" rel="noopener" target="_blank" title="">Hello Lightbulb on <a href="https://unsplash.com/search/photos/stamp?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText" rel="noopener" target="blank" title=")

In many companies, reviews (design reviews, product reviews, etc.) have the same ritual. The feature owner writes the spec. Their manager then reviews it. The group schedules a meeting to review the spec. More than once, there is a feeling that the purpose of these meetings is to get the stamp from the stakeholders rather than actually engage in an open discussion. The reasons why this can happen:

• If you already have a spec ready, why would you need 7 or so people to gather in a room and “go over” it?
• The meetings tend to be boring and can turn to be a monologue when the feature owner reads the spec they wrote.
• Sometimes these meetings tend to be nit-picky. The conversation can focus on things that are not crucial for the feature success (“why do we use int32 and not int16?”, “strings or enums?”, “tabs or spaces?”).
• Some people are more introverted than others. Are all the voices heard, or are there only a few people that are engaging in the conversation?
• The conversation on some details can take longer than expected. Time then runs out before the feature owner can cover the whole spec, sometimes even less than half of it. This can frustrating. Moreover, if a follow-up meeting is required, it can also postpone the decision making and the whole project timeline.

Be prepared with alternatives and goals, not with the solution

At my current company, we take a different approach. Reviews are made offline, using Paper (benefiting from its features like sharing, comments, tasks which makes the collaboration more efficient). Any other online editor can work.

For the design meetings, we use a different template. The decision maker chooses the 3–4 most important open questions that are critical to the feature’s success. They then compose an alternative table like we saw before. They can also recommend an alternative, but shouldn’t be very opinionated about it. The purpose of the meeting is to choose the proper approach based on the project goals.

The meeting then turns from a monologue that is focused on “stamping” a solution to an open conversation about the best approach. The audience turns from being approvers to being advisors. The feature owner doesn’t need to “defend” their selected solution. It turns into a decision maker that bases their solution on the stakeholder advice. By setting time (10–15 min) for each question, you can make sure that you cover all open questions. A decision is taken by the feature owner when the time is up.

Making sure that everyone’s voice is heard, even the introverts, is just as easy as “Hey Jane, we didn’t hear your opinion, which option do you think will serve our goals? X,Y or Z?”

So next time you want to compare two or more alternatives, replace “React.js is better than Angular” with “React.js is easier to learn, more flexible, and is updated more frequently, so if we aim to quickly ramp up new engineers and move faster with the most top-notch technologies, this should be our choice between these two”.

As for “Pineapple is the worst pizza topping” — maybe some things aren’t meant to have alternatives. ?

Thanks for spending 4 minutes of your time, until next time.

-Alon

Special thanks to:

• Eric Suh who drove the creation of the engineering review process at Dropbox
• Pierpaolo Baccichet, Steve Eisner, Gal Zellermayer, James Cowling, and Devdatta Akhawe all of whom gave valuable feedback, both as early testers of the process and as reviewers
• Rina Artstain & Keren for proofreading, reviewing this article and giving awesome technical feedback