A business is not a solitary entity existing on an island, in the dark but rather a multifarious web of interlinked functions from HR, marketing, production, to sales. Not just that, but looking outside of the business itself, there are competitors, market pressures and greater macro-economic changes led by legislation, national or global politics, and currency movements. For a business to try and make any decisions in a space so complex – it can’t be off-the-bat, without due consideration for available data. The longevity of a business and its employees could be on the line.
How to Start Measuring Data
Your data measurement capabilities and focus will be dependent on your company’s KPIs per department. Because data analysis is not business-function-specific, it means that each department can participate in analysing its own data, draw meaningful conclusions from it, and then make recommendations or reports accordingly.
There is a high level of human interaction in terms of data analysis because as much as machines can provide the data, reading it contextually is a fully human endeavour. People know exactly how a business is standing in terms of finances, human capital etc. So, only they will be able to make the best use of the data on hand in order to move your business forward. AI and machine learning rely on previous datasets and simulations, without accounting for current situations.
Data analysis as such is a desirable skillset for all employees to have across departments. Obviously, there will need to be employees who are more invested in how to interpret data, meaning they will specialise. But everyone on a team should have basic data analysis skills in order to visualise data for their job. Salespeople will need to be able to read pie charts and graphs and understand them – perhaps even draw new conclusions and create their own visualisation tools. Also, they should be able to collate information about their daily work into client reports via a dashboard (which is usually the simpler report-structure in the long-term), or custom reports created by them.
To upskill the people in your company, you could encourage them to take online courses in data analysis which will equip them with some valuable skills. Also, if your company offers to subsidise or cover the costs, it’s advisable to do this form of upskilling in increments based on your needs and budget. For robust courses, free material is not available as your employees will come out of those courses with formal training and certification.
The formality of their qualifications can then be sold to clients as a value-add for your business because clients will know that you have people who are trained and capable. There is nothing more attractive to a potential client than knowing that the people who they are trusting with their business are not just experienced but also qualified.
Some Benefits of Thorough Data Analysis
Save Yourself Time and Money
Save yourself, your business and your employees time and money. You need to try and have complete datasets to analyse in order to make informed decisions about the current state and future of your business. If you cannot account for performance and KPIs, then you’re in the dark. A great deal of time can be spent estimating and making projections, but if there is no data on hand, then it’s futile. You might as well try to extrapolate your chances of winning the lottery from all the times you’ve lost – and even there, you would be in a better position because all those losses count as a complete dataset. In terms of money: bad decisions cost real money. You can lose hundreds of thousands, even millions if your data projections are off.
Prevent Unnecessary Mistakes & Improve Insights
We’ve touched on how a mistake can cost you money. But mistakes also create complexity where there should be none and can slow down the progress of projects. This is because, for every mistake made, fixing it takes time and removes resources from other key tasks. If a junior accountant makes a mistake in balancing your books, then the senior accountant must go through their work to fix it. This oversight is a part of the senior’s job, but there are usually other, more pressing things that he or she could be doing. Being able to analyse the financial data accurately would prevent the senior accountant from having to split time between their own work and the work of the junior.
There’s also a good chance for you to get new insights into the efficacy of people in your business’s departments. You can get data related to how many people are taking sick leave on specific days, who is doing it and why, also how long people stay logged into their computers etc. You can granulate your data-gathering to whatever level you wish, if you can analyse it adequately.
Data Analysis as a Business-Critical Function
In conclusion, the gathering of data may be varied in a business but the analysis of it should follow logical pathways. Everybody on a team should be able to analyse the data related to his specific job because it will help him expand the scope implementation and base all decisions on hard facts. Estimations which emerge from accurate datasets and subsequent analysis, are more likely to be successful than those made off hunches.