Data analytics first emerged as an academic discipline in the 1990s. That was the decade when every aspect of human endeavour - from public administration to healthcare - came to rely on large sets of data for insights and decision-making.
Over time, as the volume, velocity, and veracity (the three Vs of big data) of business data increased exponentially, the practices of data scraping, data mining, and big data analysis became more common. Today, nearly 2.5 quintillion bytes of data are produced daily, with even SMEs producing and analyzing thousands of gigabytes annually. As a result, the utility of large-scale data scraping and analysis techniques has increased exponentially over the last decade.
Basic data analysis abilities are no longer considered a specialized skill set in competitive professional environments. Rather, they have become a must-have requirement no matter your particular field of work. This explains why Amazon expects almost all office employees to have a working knowledge of basic analytics skills.
This expectation might be more pronounced in certain departments or job functions, where data-driven decision-making is a core part of the work. In such cases, even employees in roles that are not traditionally associated with data analytics might be expected to have some proficiency in SQL or at least in excel spreadsheet.
The importance of analytics skills in the workplace
The ability to pore over given data to identify problems, seek out relevant patterns, identify problems, and find logical solutions has become fundamental across all rungs of professional activity. These basic capacities are as important for an order picker at a warehouse, for instance, as they are for managers and C-suite executives.
Businesses operating in highly competitive sectors and markets understand that analytical abilities represent a broader mindset and approach far more consequential than a standalone skill. They are a prerequisite for grassroots innovations at the workplace, efficiency, and the development of a company’s worth ethic and culture. Employees with functional, analytical skills are better equipped to handle negotiations, evaluations, and team-building exercises. That is why the right mix of analytical and emotional intelligence is considered a defining factor for good managers.
Let’s take a more detailed look at the factors that make analytics skills so important in the workplace:
- Problem-solving: Logical thinking, foresight, hindsight, and the ability to connect the dots are key to identifying problems and making recommendations on the best possible solutions.
- Critical thinking: Understanding what data to analyze in a given situation and evaluating it critically is necessary to reaching sound conclusions that help businesses grow and prosper.
- Creativity: Problems that require out-of-the-box solutions rely on accurate analysis of their underlying factors. Obvious solutions are not always the most effective, and it takes analytical skills to go beyond them.
- Detail-oriented big picture: Analytical skills are key to understanding how data-based recommendations will affect all aspects of a business’s operations down the line, and not just its bottom line.
- Communication: Analytical insights aid the communication of findings and recommendations across multiple teams and stakeholders, ensuring they can be put to practice most effectively.
Improving your analytical skills requires an aptitude for self-evaluation, the ability to focus on and learn from mistakes, an attitude of continuous improvement, and openness to new ideas and knowledge.
Types of analytical skills in demand at the workplace
It’s now appropriate to distinguish between two types of analytical skills. The key distinction between the two lies in how those skills are acquired:
- Hard analytical skills: These are skills that require formal training or some type of classroom education or data analytics certification. They require both a conceptual and a working knowledge of analytics tools, relevant computer skills, and statistical knowledge.
- Soft analytical skills: These are more in the nature of personal qualities developed over the course of professional employment. They are best reflected in workers who can analyze information efficiently to solve workplace problems and make decisions.
Both soft and hard analytical skills can be applied and utilized in almost every field of business operation - from management to sales, marketing, finance, planning, and accounting, among others. They are usually categorized into four distinct subsets:
- Descriptive analysis: This is all about understanding what’s happening to a given business process, function, or situation at the moment. It involves going through aggregated raw data to gather a comprehensive and accurate analysis of current trends. It helps identify patterns of behavior that can be used to make decisions and influence positive business outcomes.
- Diagnostic analysis: This discipline involves trying to fathom why something is happening. It involves multivariate analysis (based on several dependent variables) of past performance to determine the reasons behind a positive or negative development. It is primarily about identifying causal effects behind a particular phenomenon by isolating multiple probable causes and identifying those most relevant to a given effect.
- Predictive analysis: As the term suggests, predictive analysis tries to determine what will happen in the future. In terms of formal data analysis, it involves the use of statistical models and accepted forecasting techniques to predict likely future scenarios. Predictive analysis can help companies prepare for unexpected market fluctuations, seasonal changes in demand, and other similar variables in competitive environments.
- Prescriptive analysis: The final component of analytics deals with figuring out what you need to do to deliver better business outcomes. Prescriptive analysis is all about making data-driven recommendations on what actions need to be taken to achieve a specific business goal, like improving efficiency in a business operation or achieving a revenue target. It helps businesses reach strategic conclusions and focused answers to specific questions.
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