In-School Productivity Campaign | Using data analysis to improve productivity
While Growing up, we were taught to analyse everything in life in order to make an improvement; "analyse the game", "analyse your work", "analyse the problem", "Analyse!", "Analyse!", "Analyse!"
Data analysis is critical in everyday life to help you determine where there are pain-points as well as to see what needs to be done in order to reduce or eliminate them - especially in the workplace. It is a method in which data is collected and organised so that you can derive helpful information from it.
While some data analysis methods may not be highly technical or sophisticated, appropriate data analytical tools and efficient use of these tools can save time by simplifying large amounts of data into sensible and understandable information.
Some of the tools used to support data analysis range from spreadsheet to statistical packages (e.g. SPSS, R, Mathlab, Minitab, SASS, and tableau) to computer assisted qualitative data analysis software (CAQDAS).
Benefits from data analysis
By using data analysis tools, micro, small, medium and large organisations can attain various benefits from data analysis:
1. Encourages well-informed decision-making
Data analysis can back up decisions with hard evidence and provide balance in situations where opinions vary widely or emotions run high.
2. Fosters a culture of continuous improvements
Data analysis can be a great productivity driver because it can show management and business owners areas of improvement and help employees be more aware of their work activities, and help to find ways that improve how they work.
3. Delivers a competitive advantage
Companies use benchmarking as a way to compare key metrics to see where they are relative to other businesses in the industry. By analysing data, it will show what the others are doing and areas in which the company may need improvements to gain a competitive advantage.
4. Increases Profitability
A study done by the University of Texas at Austin states that "If the median Fortune 1000 business ... increased the usability of its data by just 10 per cent, it would translate to an increase in $2.01 billion in total revenue every year." The research also indicated that return on equity (ROE), return on invested capital (ROIC) and return on assets (ROA) would increase by 16 per cent, 1.4 per cent and 0.7 per cent respectively. Data analysis will help to drive down cost and increase revenue, hence increased profitability.
5. Model building
All companies need an effective business model that will assist in growth and profitability. The model-building process develops an equation by linking the relationship between different variables. By using the analytical tools, companies can develop a model which can predict future behaviour based on previous event occurrences. Predictive analysis will enable businesses to approach opportunities, mitigate risk, improve efficiency, detect fraud, develop a better marketing strategy and meet consumer expectations. A successful business model will lead to financial sustainability of the company as it will enable the business owners to keep abreast with changes in the business.
6. Drives Innovation
One of the biggest challenges that companies have to deal with when faced with innovation; is where to start working. What, first, must be done? The first stage in the innovation process is to analyse the data. Data-driven innovation can lead to new knowledge, new business opportunity, drive value creation, and foster new products, processes, and markets.
Data analysis identifies areas for potential productivity improvement based on data analytical tools. Implement data analysis as a critical part of your business and you will see increases in productivity and the overall bottomline of the business.
- Asanya Dinnall is research officer in the Research and Measurement Unit of the Jamaica Productivity Centre