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Data & Analytics – Everything You Need to Know

Big Data and Analytics

Data & Analytics - Everything You Need to Know

According to Finance Online Reports, organizations cite efficiency improvements and better decision-making as the top two benefits of Big Data & Analytics. We live in a data-rich age where one primary driver of business success is analyzing and extracting meaningful data from companies' digital insights. Nevertheless, the process and goals of data analysis may differ for different types of organizations. For example,

  • A Manufacturing Company may use data analytics to streamline its operational processes and eliminate redundancies in the supply chain.
  • A Logistics Company may use data analytics to enhance its scheduling and routing or improve delivery time to cut costs and save millions.
  • Data Analytics and Healthcare go hand in hand. A Healthcare Industry may use data analytics to predict patient behavior to ensure their safety.

However, it's only possible if businesses understand the gaps pertaining to their business - redundancies, failure of operations, etc., so figuring out how to overcome those challenges will become easy.

"Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

                    – By Geoffrey Moore, an American Management Consultant and Author.

Challenges Businesses Face in Getting Value from Insights

  • Data and business Not in Sync

Data science and business operations are frequently kept apart in organizations, leading to a lack of awareness of what is achievable on the business side and what solutions organizations require.

  • The Gap between Insight and Impact

Moving "from insight to insight-based value creation" is a vital stage that is never adequately done. Clients already understand the importance of analytics and have carried out one or more proofs of concept (PoCs) by then. These Proofs-of-Concept are kept isolated and hardly converted into effective use cases.

  • Not Aligning the Data Analytics Competence at a High Corporate Level

Data analytics can significantly impact a business only when adopted deeply and consistently across the whole organization. This type of insights-oriented transformation demands the dedication and direction of a leader with authority, and many firms still lack that degree of organizational commitment.

Did You Know?
In a report by Forrester, 74% of businesses claim to be data-driven, but merely 29% successfully connect analytics to action. Actionable insights seem to be the missing piece for these enterprises trying to leverage data to drive business growth.

A Right Strategy is What Businesses Need to Turn Data from Dull to Insightful

According to Mark Murphy, President of Softura, “It's clear that data is a crucial business asset and revolutionizes how businesses work in most sectors and industries. All enterprises must consider themselves ‘data businesses’ regardless of size and type. And since every company is a data business, they require a solid data strategy.”

Coca-Cola, a famous soft drink brand, collects customer data from vending machines that track days of the week, times of purchases made, and locations of machines to boost current consumption and sell more products, resulting in a more efficient operation that cuts costs and increases profits. In addition, getting consumer feedback via social media and other mediums allows companies to adjust their approach and better align with consumers' interests. The data companies collect aims to enhance the brand experience and expand greater customer loyalty.

A Solid Data Strategy

A good data and analytics strategy focuses on what your organization wants to accomplish and how it can help you, not on the available data. So, businesses must create a clever approach that focuses on the data they need to accomplish their goals if they want to avoid becoming overwhelmed with data. According to a senior manager at Toyota, they focus their data strategy on ensuring that it:

  • Fulfills a particular business need
  • Assists organizations in achieving their strategic objectives
  • Adds genuine value to their business

To help you understand better, here're some crucial factors to create a reliable data and analytics strategy.

How to Create a Reliable Data and Analytics Strategy?

Know Your Data Requirements

Data analysis requires a solid foundation before a business can get into the details. Analyzing data begins with determining why you need it. Along with finding a purpose, consider what metrics to track. Identify the sources of data when collecting them.

Source and Collection of Data

Data can be sourced and collected in various ways, such as through accessing or purchasing external data, utilizing internal data, and implementing novel gathering techniques.

Turn Data into Insights

It's another solid data strategy that requires you to plan to apply analytics to your data to root out business-critical insights that can improve decision-making, enhance operations, and generate value.

Technology Infrastructure Needs

The next step in developing a solid data strategy is considering the ramifications of technology and infrastructure. This is done once you have decided on the following:

  • How do you want to use data?
  • What sort of data is ideal for you?
  • How do you want to analyze that data?

Data Competencies Within an Organization

It is critical to have people with specific skillset to make the most of data. Your organization can improve data-related competencies in one of two ways:

  • By strengthening internal expertise
  • Through talent or outsourcing data analysis

"For businesses to succeed, it’s important to unlock the reams of data and utilize it to win strategically.”

                                                                           – Mark Murphy from Softura.

According to Elon Musk, proper analytics is implemented using five different technologies. These fall into the following categories:

Descriptive Analytics

‘What’s happening in your business?’ Descriptive analytics focuses on describing the current state of a business or process. It can identify what has happened and when but does not offer insight into why it occurred.

Diagnostic Analytics

'Why it’s happening in your business?’ Diagnostic analytics is a branch of analytics that uses data to derive insights and make predictions. It identifies root causes and interprets metrics that lead to actionable insights.

Predictive Analytics

Explains ‘What’s likely to happen in the future based on previous trends and patterns?’ Predictive analytics is a way of forecasting or determining future outcomes by looking at past results. It can help us to discover patterns and trends in our data that we didn't realize were there, illuminating hidden opportunities and threats.

Prescriptive Analytics

‘Helps distinguish the best course of action to bypass or eliminate future issues.’ Prescriptive analytics, also known as predictive analytics, is a data-driven technology that helps organizations make better-informed decisions in real-time.

Cognitive Analytics

Combining different intelligent technologies, such as AI, MI, etc., to perform certain tasks.’
Cognitive analytics is a highly advanced form of machine learning that uses artificial intelligence and high-performance algorithms to challenge the status quo of traditional data analysis. In other words, it is a valuable tool that facilitates the creation of better, more transparent, and more comprehensive views of all employee actions, allowing companies to distinguish the normal from the abnormal and thus leading to smarter decisions.

Benefits of Data Analytics in Business

Personalized Customer Experience

Companies collect customer data through various channels, including physical retail, e-commerce, location data, and social media. By employing data analytics to create comprehensive customer profiles, businesses better understand consumer behavior and provide a more personalized experience.

For Example, Waze, a popular Google-owned navigation app, does a remarkable job of getting you from point A to B, rerouting when traffic jams pop up, and constantly feeds advertising based on your location, driving habits, and even your Google searches. These factors elevate customer experience, which is why customers don’t mind sharing their data. The back end of these conveniences is the following:

  • Data analytics provides in-depth insights into customers' needs and preferences.
  • Storing your data in one central location and allowing your customer service team access to that data can help ensure consistency in the quality of your service.

Informed Decision-Making

Data analytics can also assist organizations in driving business decisions. While predictive analytics can forecast what may happen in response to business changes, prescriptive analytics can suggest how such changes should be handled. For instance,

  • Prices or product offers can be changed to see how they affect clients’ demand.
  • A/B testing of these changed products or offers can then be done to validate hypotheses derived from such models.
  • Organizations can use data analytics consulting to evaluate the performance of the adjustments and visualize the outcomes after gathering sales data on the revised products. This will assist decision-makers in determining whether or not to implement the changes across the company.

Streamlined Operations

Data analytics can help organizations increase operational effectiveness and do a great job at predicting outcomes. For example,

  • Data collection and analysis involving the supply chain can tell the source about production delays or bottlenecks and help predict potential future issues.
  • An organization could replace this vendor if a demand forecast indicates that it won't be able to manage the volume needed for the holiday season. This would prevent production delays.

Enhanced Security

According to Gartner, businesses will be attacked by malware and experience interruptions to their business. Organizations can use data analytics to establish the root causes of previous data breaches by analyzing and visualizing pertinent data.

  • For instance, the IT division can employ data analytics programs to analyze, process, and visualize audit logs to determine the point of origin and the course. IT can further use this information to find vulnerabilities and patch them.
  • To stop upcoming threats, IT departments might also utilize statistical models. Attacks frequently entail strange access patterns, especially load-based assaults like a distributed denial-of-service (DDoS) attack. Organizations may build these models to run continually, with monitoring and alerting systems added on top to find and highlight anomalies so security experts can act immediately.

It's Time to Realize the Benefits of Data and Analytics

According to Market Research Future, the data analytics market generated a revenue of USD 22,998.8 Million in 2020 and is expected to outreach a market value of USD 346.24 Billion by 2030, growing at a CAGR of 30.7%. This clearly indicates that the growth of data and analytics will only gain momentum in the future and will be at the core amongst other countless technology solutions. So, businesses must seek advanced data analytics to achieve organizational efficiency, customer engagement, or marketing efforts.

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