A Two-Tiered Approach to Elevate Business Analysis

Data analytics has emerged as a cornerstone for success that will only increase as we move into the future. It's more than just a buzzword; it's a pivotal tool that enables organizations to decipher the vast amounts of data at their disposal. By understanding trends and patterns within this data, businesses make more informed decisions, gain a competitive edge, and unlock new opportunities. In this article, I want to provide a differentiation between two levels of business analysis that goes into strategic planning.

The Problem

Data analysis is not new; however, the acceleration of tool development to maintain a competitive advantage is the challenge. Many organizations do not have the financial resources to integrate these new tools and may not have the human resource capacity to retain talent full time or upskill existing staff in the art of data analysis.

Organizations collect tons of data, but beyond basic financial reports and CRM reports, the ability to gather next level insights is still a concern for many leaders. Large organizations have a lot of data, but may lack the talent to do true business research while integrating the data sources to answer key business questions. They may end up simply creating a dashboard that summarizes high-level information. Small and medium organizations may lack the tools to capture data in one dashboard much less be able to have an analyst on staff.

Without a data strategy, the ability to look at the business as a whole is lost and leaders revert back to hunches and feelings. Nevertheless, in the ever-evolving landscape of technology and business, the ability to obtain a competitive advantage starts with data.

Here are two levels?that leaders should consider when answering key business questions:

1. Basic Data Review

At its core, data review is a primary analysis that allows one to understand past performance. Primary analysis ?provides a summary of results that occurred in a particular timeframe. It utilizes descriptive statistics which focus on measures of central tendency. These may consist of averages, percentages and totals. An example of primary analysis is a financial report like an income statement or profit and loss statement as it summarizes information. For instance, consider a retail business scrutinizing its last quarter's sales data. A primary analysis would show that the company generated $38,500 in revenue and 301 customers who spent on average $128 each.? Through descriptive analytics, the business can identify which products were bestsellers, what times of year sales peaked, and which marketing campaigns were most effective or the number of employees that responded to a particular survey question. This retrospective view is crucial for businesses and is just the beginning to understanding their journey and measure their growth and impact over time.

?2. Advanced Data Insights

While descriptive statistics offers an overview, secondary analysis offers data insights that delve deeper into the data. It provides the why? to key business questions. For example, a sales leader may ask why sales are declining, while the number of customers remain unchanged. An analyst may show that the sales are declining because the customers are spending less per transaction. Meanwhile an employee engagement survey response indicates that sales staff morale has declined and they are reluctant to ask for an upsells since the cap on commission was instituted. Data insights looks a multiple sources of information to identify root causes and infer causation. Secondary analysis uses advanced statistical tools and focuses on correlations, quantify the extent of relationships, and when combining data from multiple periods, predict future outcomes. It can identify useful key performance indicators (KPI), and help you identify poor KPIs. ??This type of analysis is pivotal in making predictions and informed decisions. For example, in the context of the same retail business, data insights might reveal how customer purchasing behaviors correlate with age, income, or even seasonal changes or even net promoter scores. This level of analysis is instrumental in shaping future strategies, from personalized marketing to inventory management.

?The Role of Talent with Analytical Skills

The role of a business analyst transcends mere number crunching. These professionals are the architects who transform raw data into meaningful insights. They ask unbiased and below-the-surface questions. The are skilled in quantifying non-numerical data, and setting benchmarks in KPIs and balanced scorecards. They help businesses understand not just what has happened, but tell the story as to why it happened and what might happen in the future. Furthermore, they free up time for executives whose time should be spent working on next level business/corporate strategy. In a world where data is continuously generated, the insights gleaned by these analysts can lead to breakthrough innovations, efficiency improvements, and more targeted customer or employee engagement strategies.

Case Study

For example, I was researching data for a company that was developing its human capital strategy. The client wanted to understand why there was a lack of Group 1 in Senior leadership roles over a 10 year timeframe. The organization had what I classified as junior level management (supervisors, general managers), middle management (regional and district managers), Senior Management (Directors and Vice Presidents), Executive Management (Chief Level).? There was good representation in Junior management roles for both Group 1 and Group 2. However, we found a steep decline in percent representation between Junior management and middle management. ?Further investigation revealed tenure to be a key differentiator between Group 1 and Group 2 in junior management roles; whereas Group 1 stayed on average 1 year less than Group 2 that were more likely promoted into Middle Management roles. Tenure was identified as a root factor, which led to further questions and focus groups. Further insight showed ironically that Group 1 work longer hours and burned out more quickly. Eventually, the Executive team decided to focus on retention strategies, employee assistants programming, and management development program that increased the likelihood of promotion into junior management roles. Furthermore, we saw an escalation of callouts in Group 1 during the months preceding their final day which could be used as a leading indicator for intervention.? By focusing on this level where the sharpest declined existed, this would increase the probability of diversity into senior leadership roles over time; however, in the meantime, much needed support is provided to people who needed it the most!

My Work Through Nortal

I provide management consulting on a number of business related challenges. This requires a deeper level of business analysis which is quite cross functional and multi-industrial. As a seasoned researcher and business analyst, I continually review best practices and work with clients on bespoke data analytics solutions using state-of-the-art tools to help them solve problems and identify root causes. Whether it's through engagement survey administration, CRM or ERP report integration, business-level predictive modeling for presentations, customer and human resource analysis, or labor market trend analysis, my aim is to empower businesses with data-driven insights. I don't just provide data analysis; I offer a roadmap to harness the power of your data effectively.

I invite you to engage in this conversation. Share your experiences with data analytics, ask questions, or express your thoughts in the comments below. If you're looking to delve deeper into the world of data analytics and understand how it can transform your business, let's connect.

For more insights or to learn how Nortal Consulting can help your business thrive with bespoke business solutions feel free to reach out to me at [email protected] or visit our website www.nortalconsulting.com