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.
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.
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.
Also, the four biggest benefits of data analytics are:
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.
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.
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.
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.
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.
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.