What is being data driven?
We hear the term data driven all the time but what does it really mean? I will try to explain it simply. Data driven means that taking decisions based on on the empirical evidence rather than acting on gut instincts or speculation. Adopting to data driven decision making means all processes and decisions will be based on the data.
Data driven vs Instincts based decision making
Today many of the successful companies around the world, base their decision making on hard empirical evidence gathered by analysing the data. Those companies gained advantage over their competitors who are using instinct based decision making. The reason why data driven companies are achieving more success is because their decision making relies on the empirical data with no subjectivity or bias. Relying on just business acumen and gut instincts is not always the best option especially considering that world we are leaving right now is dominated by the technologies advancements which allows companies to be even more data driven.
Advantages of data driven decision making
Consistency: In some companies gut instinct really works. Some decision makers are really good at what they do and those managers are the competitive advantage for their organisations, they have unique thinking and vision. But there is one problem with this, If these decision makers leave the company their successors might not be successful as their predecessors. If the organisation was data driven though, success of the company would not be dependent on one person, data driven decision making creates a consistent success.
Receptiveness: If the company is data driven its more likely that they will be more responsive because they would have kept track of their data, therefore they could analyze this data to predict the patterns and trends. For example if a certain company has a very cyclical sales patterns, management can realise which season their revenues will start to go down and they can adjust their spending accordingly.
Faster decision making: Compared to gut instinct decision making, data driven decision making is a lot faster and confident. Reason is obvious, data driven decisions are based on the facts ands data, everything is present in data, this doesn't mean that all of the decisions will take away human factor and gut feeling but it just means that decision makers will get to see everything they need to see in data adn than use gut instinct to take a decision
Cost cutting: If a company is keeping track of every activity they do, its is more likely that they will see what is working or not. For example by keeping track of expenses, they could see whether they have unnecessary spendings or not. Based on the historical data, they can predict when their business will slow down and than make the necessary adjustments to their spendings to prevent any unnecessary spending during the slow down period.
How to be more data driven?
1) Educating your team about benefits of being data driven
In order to be more data driven, everyone inside the organisation should know about the benefits of switching to data driven decision making. It is hard change the mind of an industry veteran who has spent 20 years in the industry and earned his spot in the company by solely trusting his guts. I am not saying that these people are doing something wrong or bad, actually most of these people are very hardworking and smart. But they need to be taught that there are better and easier ways to what they do, they need to see the benefits of being data driven and believe in it, so that they could change their mindsets. Change should start with the people.
2) Purchasing the right tools
Okay lets say that first step of being more data driven is completed, you have educated your employees in the company about the benefits of being data driven. Now it is time to get the right tools to be more data oriented. Business Intelligence tools are the best way to go, they allow centralised data portal where all employees inside the organisation can benefit from it. Doing this will allow teams to have better insight on what is going on and also detect any issue start working on it.
3) Learning how to interpret the data
Having all that data at your disposal is good but it is not enough. You need to right kind of people to analyze and interpret all that data. Each business needs a different metrics to utilise the data, it is important that your data team knows about which metrics to use so that they can create a strategy to reflect the right dataset to the right teams.
4) Use data to make better decisions
This is the most important step, you educated your people about being data driven, you convinced them that data driven decision making is better, you chose the right tools and right people to use them and this is great. But all of these means nothing if you do not align your data with your business objectives and use the data harvested to make better and faster decisions. You could have the best data in the world but if you are merely using it to just to look like fancy data driven company, then you are wasting your money and efforts for nothing. Data needs to be used in the top level decision making and this mindset should be embedded inside the organisation.
Examples of using data to make better decisions
E-commerce: These businesses can benefit a lot from being data driven. Simple example would be that a specific e-commerce company is having a low conversation rate even though they have high number of customers. Using the funnel feature they can see where the bottleneck point is, they can see where the users churn and abandon the current process. In our case it could be that company is not offering commonly used payment methods or they have some hidden shipping fees which becomes visible to the customers in checkout process hence they abandon the transaction, therefore leading to low conversation rate.
Gaming: Especially for freemium games it is really important to keep people coming back to their app after their initial use. Since freemium game companies makes money from the ads, they need a wider audience to generate more income. For example, lets say that a specific gaming has games on android and iOS, using retention feature company can see whether their users will come back and play their games after the initial experience. If the retention rate is lower, lets say on android it could indicate that there are problems with the android version, maybe it is less playable on the platform etc..
There are many more advantages of being data driven, to keep it short I just gave two of them. Being data driven has become a necessity for the corporations in todays world and this is backed by the ever advancing technology.