Data Driven Decision Making Series - Part 2
How can you benefit from data-driven decision-making?
What business decisions can I use data for?
There is no doubt that you can benefit from data-driven decision-making. How do you go about using the data in your organization to make the decision? It is important to identify the key problems for which you can find solutions using data.
For example, you can use data to find out:
- Finance: What’s the most cost-effective way to hire new staff, or the cheapest way to promote a new product?
- Growth: What activities can you do to prevent churn? How do you improve customer loyalty? Are the new features you’re planning likely to impact your business’ goals?
- Marketing and sales: Which advertising channel gets the best ROI? Which sales activities generate the most leads?
- Customer service: What’s the most cost-effective way to handle support tickets? Which channels improve response times?
Applications of Data-Driven Decision Making
Here are two simple examples that show how you can apply data-driven decision making in your organization. The first talks about finding the best strategy for launching a new feature or product on the market. The second tries to find the cheapest solution for hiring new employees.
#1: Market Launch Strategy
Let’s say you want to launch a new product and are looking for the best strategy. Instead of picking one and hoping for the best, you can use a data-driven strategy to find the optimal marketing strategy.
You can use data from previous market launches to predict the success of a particular strategy. Let’s say you have data about the number of sales per product. From this data, you can partially determine the effectiveness of each campaign and decide on the best one. Try to incorporate as many relevant data points as possible to make the smartest decisions.
#2: Cost-Efficient Hiring
Now let’s assume you want to hire a new employee. There are tons of options. As an organization, you can decide to outsource recruiting to an agency or do it in-house. In-house hiring would mean you carry out interviews yourself and you try to find a cost-effective method for reaching the right candidate.
To figure out the best approach, you need data to decide what method to use. First of all, you can access past hiring data and the costs associated with the methods you’ve already used. Next, you can look for official reports or studies that can reveal which is the best approach for your organization.
Benefits of Data Driven Decision Making
1. Reduced Costs
You can reduce costs if you can make better decisions, such as deciding whether or not to develop a feature that your users really want instead of using intuition and guessing wrong. One good approach is using a questionnaire to learn what users want.
On the other hand, don’t neglect the extra hidden costs of implementing data-driven decision making. You’ll also need to do the following:
- Buy storage for all your data
- Purchase licenses for data processing, data management, and data analysis tools
- Hire new employees such as data scientists
- Teach employees how to capture data and how to use tools that might be new to them
In the end, the benefits will outweigh the costs and help you stay ahead of your competition in a competitive, fast-moving market.
2. Increased Speed of Decision Making
Everyone has their own opinions, so important decisions often require many iterations and conversations. When a decision is backed by hard data, there is less room for disputing the likely outcome. Being able to swiftly make decisions is a big advantage for an organization, especially in a competitive market.
3. Stimulate Continuous Improvement
Another benefit of data-based decision making is that it indirectly leads to continuous improvement. In order to implement data-driven decision making, your organization needs to capture data. Data capturing can be done by measuring your application using various metrics, giving you much better insights. These increased insights help you improve your product faster, increasing the overall efficiency and performance of your teams.
4. Shift How Teams Make Decisions
Most companies rely on senior, knowledgeable, experienced leaders. However, these people are only human and don’t always make the best decisions. Data-driven decision making shifts the way teams make decisions since they rely less on skilled people and more on data analysis and metrics.
In other words, teams shift from hierarchical decision making to a more open, collaborative form of decision making where data is central.
5. More Confident Decision Making
Data-based decision making helps your organization make more accurate, measured decisions. As a side effect, your organization can also feel more confident. For example, if a user survey shows that more than half of your users want a certain feature, there will be no doubt that you should implement it and no fear that users won’t like it.
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