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How Data Analytics Can Improve Company Performance

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The business intelligence and analytics industry reached over $ 19 billion globally in 2020, albeit the derailed economic performance caused by the pandemic.  The business intelligence market growth experienced a 5.2% increase, and the data analytic growth rate is expected to rise in the coming years as companies realize the need to manage data to make better decisions.

According to Angela Ahrendts, a former retail Vice President at Apple Inc., customer data is the most significant differentiator among businesses in this era. Companies that know how to maneuver heaps of data to create strategic moves usually succeed. To determine how companies adopt and implement data analytics, let’s first understand how data can make a company’s operations efficient. 

Data Analytics: Four Ways to Increase Company Performance

As discussed earlier, data analytics is beneficial for making more accurate business decisions. Managers and executives can take action on the data insights they get to drive better competitive advantages in their markets. There are four ways data analytics can accelerate business performance:

The first way is by creating informed decisions. One of the key benefits that businesses look out for when dealing with data analytic solutions is developing better and more accurate decisions from the insights they get from analyzing data. 

There are two processes that ensure the development of better decisions: predictive analytics and prescriptive analytics. Prescriptive analytics are utilized to project the way companies react to forecasted trends, whereas predictive analytics focus on events that might occur after analyzing collected data.

Improving efficiency is another route. Data analytics is highly beneficial especially in the operation management for streamlining operations. For example, companies can retrieve and assess their data relating to supply chains to discover where delays in their supply networks happen or to forecast areas where problems emerge and use these insights to prevent any issues.

Data analytics also enables risk mitigation. To cut down losses, data can be utilized to reduce physical and financial risks in business. Through collecting and assessing data, inefficiencies can be either identified or predicted. Also, potential risks are revealed to inform management on creating preventive policies. 

Lastly, data analytics enhances security. As many businesses confront numerous data security threats in today’s era, it is essential to keep the company’s cybersecurity out of dangerous attacks that cause financial or brand image blow. A company can evaluate, process, and draw insights from its audit logs to showcase the source of previous cyber breaches. The outcome of this exercise would be to recommend possible remedies to the problem.

Join The KPI Institute’scertification course on data analysis today to learn more about data analytics, improve your analytical skills and make wise business decisions.

Empathy: Is It an Overrated Concept or a Powerful Business Skill?

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Empathy has started to become one of the most essential skills that management should foster amongst their leaders. The Center for Creative Leadership conducted a study that included 6,732 managers in 38 countries and concluded that empathy has a positive impact on job performance. Namely, bosses perceive their subordinates (managers) who practice empathetic leadership as better performers in their jobs and it has proved to have a vital role across the business functions, such as Marketing, Customer Service, and Human Resources. Ultimately, it showed that embracing empathy within the culture of the workplace can positively influence the employees’ job satisfaction. 

Empathy and Marketing/Product Development

In marketing, trying to understand your customers and putting yourself in their shoes, will definitely help you to better understand their needs. Consequently, this would help in creating and promoting the right products and services for the right customers. Empathizing is actually the first step in the design thinking process, which includes understanding the customers before you start to design your product. According to Stanford, empathy is an integral aspect when designing a human-centered process, and it further explains that  the “Empathize mode is the work you do to understand people, within the context of your design challenge.”

Empathizing means observing, engaging, and listening to your customers; it does not focus only on talking with your customers and getting insights from interviewing them. It is about putting yourself in the customers’ shoes to try and figure out their pain points and thoughts concerning their attitude and behavior with a specific product/service while still having the perspective of a marketer or product developer. Marketers or product developers might even reach conclusions that could lead them to a whole new product that would actually create a need that their target market has not thought of.

An example that could illustrate this is IKEA’s marketing strategy involving products of flat packs and self-assembly furniture. One of the company’s frontline workers found difficulty in trying to get a table into his car, so he took the legs off to make the table fit. This led to an empathetic insight that consumers might be facing the same problem. To address the issue, IKEA initiated flat packs and self-assembly furniture. This example highlights empathetic reasoning in which employees are keen to put themselves in the shoes of customers, resulting in higher market performance. 

Empathy and Customer Service

If you want to better serve your customers and solve their problems, empathy is the main key to a better customer experience and should be embraced in a customer service function’s strategy and culture. When customer service agents answer their clients, whether it is over the phone or face-to-face, they should show that they care about solving their clients’ issues and offer better alternatives. This is one way of keeping their customers and turning them from one-time purchase customers to loyal ones. 

Talking and listening to your customers in an empathetic way is one of the strategies that will enable customer service functions to handle difficult customers while gathering more data and insights. This could help other departments in improving their products and services, such as adding more features or even coming up with new solutions. Empathetic behavior in customer service also helps organizations in maintaining good relationships with their customers, especially for industries that rely on the customers to create their image of the organization through their customer service agents.

Empathy and Human Resources

Dealing with your employees in an empathetic manner will definitely have a positive impact on their job satisfaction and performance. Empathy should be involved across the different HR areas and not just in communicating with employees, such as feedback meetings or training and development programs. Having an empathetic attitude will enable HR people to gather more data for developing better rewards, benefits systems, and training and development programs. Moreover, embracing an empathetic attitude will enable HR functions to foster inclusion and diversity in the workplace, which is one of the top priorities for HR leaders and managers.

Empathy in HR has never been more important than today as people and businesses around the world are trying to recover from the effects of COVID-19. Encouraging and supporting managers and leaders to practice empathetic listening with employees is not a waste of time. While leaders and managers do not have to agree with everything being said by their employees, it is imperative for them to show their employees that they care about their opinions, ideas, and thoughts. With the challenges of remote working amongst others, empathy has become vital as it increases the employees’ sense of belonging and appreciation in the workplace.

However, some business owners might think that empathy is overrated and can have a negative impact. For instance, some managers or leaders may think empathy could cause emotional and psychological burdens that could lead to burnout. Moreover, it might even lead to poor decision-making as it encourages managers and leaders to be emotionally involved which may push them to make wrong decisions rather than focus on data and facts. Furthermore, some organizations might be worried that empathy may create a messy or chaotic environment to work in; structured and professional feedback meetings, for instance, may turn into informal chats. 

Conclusion

Everything has its pros and cons, but it depends on how the organization embraces empathy in the workplace and to what extent. It is essential that organizations differentiate between empathy and sympathy as the two concepts are completely different. It is the responsibility of HR people to highlight the difference between the two concepts starting from the top management to the most junior person in the workplace. Moreover, setting the limits of practicing empathy in the workplace is essential; it is not about agreeing to everything being said by the employees or giving false promises, but it is about listening and making an effort to understand what the other person is trying to explain to reach a decision that can benefit both employer and employee.

Like any skill, empathy is good up to a certain extent. Organizations need to understand how they want to involve it in their culture and in what sense. HR functions should provide sessions/workshops or training sessions that explain the definition of empathy and the methods of practicing it. HR functions also should monitor how leaders and managers are practicing empathy within their functions and how their employees are perceiving it.

Data Visualization as a Form of Sculpting

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“If communication is more art than science, then it’s more sculpture than painting. While you’re adding to build your picture in painting, you’re chipping away at sculpting. And when you’re deciding on the insights to use, you’re chipping away everything you have to reveal the core key insights that will best achieve your purpose,” according to Craig Smith, McKinsey & Company’s client communication expert.

The same principle applies in the context of data visualization. Chipping away is important to not overdress data with complicated graphs, special effects, and excess colors. Data presentations with too many elements can confuse and overwhelm the audience. 

Keep in mind that data must convey information. Allow data visualization elements to communicate and not to serve as a decoration. The simpler it is, the more accessible and understandable it is. “Less is more” as long as the visuals still convey the intended message.

Finding the parallel processes of exploratory and explanatory data visualization and the practice of sculpting could help improve how data visualization is done. How can chipping away truly add more clarity to data visualization?

Exploratory Visualization: Adding Lumps of Clay

Exploratory visualization is the phase where you are trying to understand the data yourself before deciding what interesting insights it might hold in its depths. You can hunt and polish these insights in the later stage before presenting them to your audience.

In this stage, you might end up creating maybe a hundred charts. You may create some of them to get a better sense of the statistical description of the data: means, medians, maximum and minimum values, and many more. 

You can also recognize in exploratory if there are any interesting outliers and experience a few things to test relationships between different values. Out of the 100 hypotheses that you visually analyze to figure your way through the data in your hands, you may end up settling on two of them to work on and present to your audience.

In the parallel world of sculpting, artists do a similar thing. They start with an armature-like raw data in designing. Then, they continue to add up lumps of clay on it in exploratory visualizations. 

Artists know for sure that a lot of this clay will end up out of the final sculpture. But they are aware that this accumulation of material is essential because it starts giving them a sense of ideal materialization. Also, adding enough material will ensure that they have plenty to work with when they begin shaping up their work.

In the exploratory stage, approaching data visualization as a form of sculpting may remind us to resist two common and fatal urges:
  • The urge to rush into the explanatory stage – Heading to the chipping away stage too early will lead to flawed results.
  • The urge to show all of what has been done in the exploratory stage to the audience, begrudging all the effort that we have put into it – When you feel that urge, remember that you don’t want to show your audience that big lump of clay; you want to show a beautified result.

Explanatory Visualization: Chipping Away the Unnecessary

Explanatory visualization is where you settle on the worth-reporting insights. You start polishing the visualizations to do what they are supposed to do, which is explaining or conveying the meaning at a glance. 

The main goal of this stage is to ensure that there are no distractions in your visualization. Also, this stage makes sure that there are no unnecessary lumps of clay that hide the intended meaning or the envisioned shape.

In the explanatory stage, sculptors use various tools. But what they aim for is the same. They first begin furtherly shaping the basic form by taking away large amounts of material. It is to ensure they are on track. Then, they move to finer forming using more precise tools to carve in the shape features and others to add texture. The main question driving this stage for sculptors is, what uncovers the envisioned shape underneath?

In data visualization, you can try taking out each element in your visualization like titles, legends, labels, colors, and so on. Then, ask yourself the same question each time, does the visualization still convey its meaning? 

If yes, keep that element out. If not, try to figure out what is missing and think of less distracting alternatives, if any. For example, do you have multiple categories that you need to name? Try using labels attached to data points instead of separate legends.

There are a lot of things that you can always take away to make your visualization less distracting and more oriented towards your goal. But to make the chipping away stage simpler, C there are five main things to consider according to Cole Nussbaumer Knaflic as cited in her well-known book, Storytelling with Data
  • De-emphasize the chart title; to not drive more attention than it deserves
  • Remove chart border and gridlines
  • Send the x- and y-axis lines and labels to the background (Plus tip from me: Also consider completely taking them out)
  • Remove the variance in colors between the various data points
  • Label the data points directly

In the explanatory stage, approaching data visualization as a form of sculpting may remind us of how vital it is to keep chipping away the unnecessary parts to uncover what’s beneath, that what you intend to convey is not perfectly visible until you shape it up.

Overall, approaching data visualization as a form of sculpting may remind us of the true sole purpose of the practice and crystalize design in the best possible form.

Sign up for The KPI Institute’s Certified Data Visualization Professional course to learn the fundamentals of creating visual representations, the most effective layouts, channel selection, and reporting best practices.

CRM and What It Can Manifest Into Your Business

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The CRM process is a business technique that allows firms to better identify and comprehend their customers. Often, Customer Relationship Management (CRM) programs and methods are used to gather the information needed to understand the current experience of a customer. CRM systems typically collect and store information about potential and current customers, which makes them very useful for both marketing and sales processes. 

Recently, almost all companies use CRM to achieve their business goals. It is reported that 65% of companies implement a CRM software platform within the first five years of operation, indicating a clear need for solutions to help companies manage large volumes of customer data. Of course, this type of CRM is different from B2C (business to customer) management software because B2B and B2C companies live in different realities. 

The Objectives of CRM

CRM systems collect customer data through various channels or points of contact between the customer and the company, which may include your company’s website, phone calls, live chat, direct mail, marketing, and social media. Companies are trying to integrate social CRM data with other customer data from sales or marketing to get a single view of their customers. These systems collect data about customers and the organization’s interactions with those customers. Many CRM systems are capable of tracking customer interactions and developing relationships from first contact to final sale and beyond, providing a 360-degree view of customer relationships.  

When marketers or salespeople learn more about a customer, CRM information tells them details such as who the customer is, how the company found the customer, and what information they requested. From there, they can anticipate people’s needs and set up the next set of interactions to help your company progress in the adoption process. With all the necessary customer data, CRM tools allow you to perform this process. CRM solutions can display past customer and contact patterns, giving marketing teams a clear picture of their target audience. Although CRM may seem like an internal process, customers will have the best experience with you. 

Analytics in CRM helps improve customer satisfaction by analyzing user data and helping you create targeted marketing campaigns. Quickly discovering the benefits associated with CRM initiatives means a better understanding of who the customer is and how best to talk to them. The best customer support system is a key strategy for influencing the customer to support the company. 

The overall business goal of a CRM system is to help an organization: 

  1. Attract new prospects and guide them through the sales process.
  2. Maintain and manage relationships with existing customers to maximize their lifetime value to the company.
  3. Increase productivity and reduce overall marketing, sales, and customer management costs.

Meanwhile, the goal of a CRM process is to improve a company’s marketing efforts, product development, customer service, and sales. 

Conclusion

CRM can help you identify customer needs, track feedback, and manage customer service improvement. One possible strategy for improving CRM in your business is to serve customer-centric goals. Be prepared to test different ways you can use CRM to achieve your business goals. Get in touch with the experts to help you in choosing the right solution so you can have a completely customized CRM system. 

How Data Enrichment Can Help Us Use Big Data Better

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Big data is a major asset for businesses that can access its insights. Making this happen, though, is a complicated job that needs the right tools. Enter data enrichment.

Understanding how it works and its impact on current industries is a great way to get to know what data enrichment can do for your organization. How it benefits the use of big data will become clearer, too.  

What Is Data Enrichment? 

Data enrichment is the process of identifying and adding information from different datasets, open or closed, to your primary data. Sources can be anything from a third-party database to online magazines or a social network’s records.

People and organizations use data enrichment to gather legitimate intel on specific things, like a customer, product, or list of competitors. And they can start with just their names or email addresses.

As a result, the original data becomes richer in information and more useful. You can find education trends, profitable news, evidence of fraud, or just a deeper understanding of users. This helps improve your conversion rate, customer relations, cybersecurity, and more.

The most popular method of making all this a reality is specialized software. Their algorithms vary in strengths and weaknesses, as SEON’s review of data enrichment tools shows. They can target human resources, underwriting, fraud, criminal investigations, and more. However, the goal is the same: to support the way we work and give us better insights.

Data Enrichment and Big Data: What Statistics Say

Data enrichment is a good answer to the problem of big data, which often sees masses of disorganized and sometimes inaccurate information that often needs cleaning, maintenance, and coordination. 

A 2021 survey by NewVantage Partners on data-driven initiatives highlights some key difficulties in using big data for corporate improvement. These challenges include:

  • Managing data as an asset
  • Driving innovation
  • Beating competition
  • Creating a data-driven culture within organizations

Despite the benefits of smart data management and major investments already in place, only 24% of firms have become data-driven, down from 37.8%. Also, only 29.2% of transformed businesses are reaching set outcomes.

What this shows is that, yes, big data is difficult to deal with but not impossible. It takes good planning and dedication to get it right.

There are several promising big data statistics on FinancesOnline. For starters, thanks to big data, businesses have seen their profits increase by 8-10%, while some brands using IoT saved $1 trillion by 2020. 

Also, the four biggest benefits of data analytics are:

  • Faster innovation
  • Greater efficiency
  • More effective research and development
  • Better products and services

These achievements are taken further with data enrichment, which adds value to a company’s datasets, not just more information to help with decision-making.

How Does Data Enrichment Help Different Industries? 

The positive impact of constructively managing data is clear in existing fields that thrive because of data enrichment and other techniques. Here are some examples.

Fraud Prevention

Data enrichment helps businesses avoid falling victim to fraudsters. It does this by gathering and presenting to fraud analysts plenty of information to identify genuine people and transactions.

For example, you can build a clear picture of a potential customer or partner based on information linked to their email address and phone number. Do they have any social media profiles? Are they registered on a paid or free domain? Have they been involved in data leaks in previous years? How old are those? 

It’s then easier to make informed decisions because we know much more about how legitimate a user looks.

Banking services, from J.P. Morgan to PayPal, benefit from such intensive data analytics, as do brands in the fields of ecommerce, fintech, payments, online gaming, and more. 

But so do online communities, where people create profiles and interact with others. For example, fake accounts are always a problem on LinkedIn, mainly countered through careful tracking of user activity. Data enrichment can help weed out suspicious users in such communities, keeping everyone else safe.

Marketing

Data enrichment in marketing tracks people’s activities and preferences through cookies, subscription forms, and other sources. To be exact, V12’s report on data-driven marketing reveals Adobe’s survey findings regarding what data is most valuable to marketers.

  • 48% prefer CRM data
  • 40% real-time data from analytics
  • 38% analytics data from integrated channels

Companies collect this data and enrich it to create a more personalized experience for customers in terms of interactions, discounts, ads, etc. Additionally, brands can produce services and products tailored to people’s tastes. 

HR

The more information your human resources department has, the better it’s able to recruit and deal with staff members. Data enrichment is a great way to build strong teams and keep them happy.

Starting from the hiring stage, data enrichment can use applicants’ primary data, available on their CVs, and grab additional details from other sources. Apart from filling in any blanks, you can flag suspicious applicants for further investigation or outright rejection.

As for team management, data enrichment can give you an idea of people’s performance, strengths, weaknesses, hobbies, and more. You can then help them improve or organize an event everyone will enjoy.

Summing Up

As we saw in these examples, data enrichment already contributes to the corporate world in different ways, both subtle and grand. 

With the right knowledge and tools, we can tap into this wealth of information even further, allowing it to make a real difference in how we work and what we know, rather than simply amassing amorphous and vast amounts of data.

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About the Author

Gergo Varga has been fighting online fraud since 2009 at various companies – even co-founding his own anti-fraud startup. He’s the author of the Fraud Prevention Guide for Dummies – SEON Special edition. He currently works as the Senior Content Manager / Evangelist at SEON, using his industry knowledge to keep marketing sharp and communicating between the different departments to understand what’s happening on the frontlines of fraud detection. He lives in Budapest, Hungary, and is an avid reader of philosophy and history.

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