Through my years of experience, I worked with big companies in which the business analytics was very established, but also with startups, that just began their analytics journey.
Learning from each one of these companies, in their different analytics maturity levels, I understood that there are a few success factors for the analytics in a company.
So what are these factors? what should you pay attention to when considering analytics in your business?
- Company’s commitment– well, to my opinion, this is the most important thing- a company should not start working on the analytics, if there is no commitment from its management. What is this commitment? it is actually two commitments:
- Data- Driven decision making- a commitment to start making decisions based on data and facts, rather than on gut feeling and assumptions
- Long-term commitment- Business analytics is not a one-time project, it’s a journey- it can be done in small steps, and in a slow pace, but it is still a journey- in order to benefit from all the advantages in an established analytics platform, the company needs to invest time and resources, same as it invests in other domains , such as product or marketing. Business analytics should have the right importance level in the company’s priorities
- Timing-many times, I’m being asked by startups and small companies, if it’s not too early to add analytics to the business. So, what is actually the best time to start working on your analytics? My approach is that the sooner you can, the better! the sooner you start thinking on measuring your activity, and planning your product and marketing in a way that you can later also measure it, the easier it will be afterwards. Planning your product and marketing efforts thinking of how you measure it eventually, will allow you to go live with your product and measure it from the start. It will allow you to save history and more data , that will eventually enable you to make more complicated analyses and predictions in an early stage. Businesses today have to act fast! having the data you need for making decisions, will allow you to do that. And for a start, you don’t need to have the most developed and complicated analytics platform- start with collecting the minimal data that you need for answering your first questions, analyse it without complicated analytics tools, take it in small steps, but start working on it from the start. It really makes a big difference!
- Technology– choosing the right tools that will answer the business analytics requirements is fundamental for the success of the analytics in the business. By tools, I refer to both back-end and front-end tools.
- The technology should fit the long-term plans and strategy of the company, will be agile and adjustable to the company’s growth and changing needs
- Different data sources and data types require different technologies- Is most of your data unstructured or structured? what is the volume of data that you expect to have? how many data sources do you expect to have? who will be the analytics users in the company and what is the visualization level that will best fit their needs?
- Data quality– Usually the data is not in the form we actually need it to be. One of the main challenges of analytics is the cleaning of data- this can be a very frustrating and time consuming task. Data quality should always be on our mind in the product planning- how do we make sure the email addresses we collect can be analysed? how do we make sure we don’t just get free text in the registration form? these questions and more should be thought of right from the beginning, making sure that we can measure all of our activity and data that is collected.
- Skilled analysts– that understand the business and the technology. While this sounds obvious, this is many times what determines the success/ failure of the analytics in the business. It’s very important to use an experienced professional, with a broad business acumen, that can align the analytics to the company’s strategy and direction. An experienced professional will build the analytical capabilities, and translate the data and analytics “language” into a clear picture and call for action for the different units and positions in the company. I’ve seen companies that have teams of analysts, that produce reports and provide data/information to the business managers, but this is not enough! a good analyst is an analyst that provides recommendations, and actionable business insights, not just data/ reports.