6 Tips to Enhance Your Data Analysis StrategyDecember 26, 2019 by Jorge Ignacio Gómez
When we’re thinking about smart decisions, the first thing that comes to our mind is which data we have and which data we need to collect. Always it’s better to make informed decisions than doing inaccurate suppositions.
Consequently, a data-driven company plans its business strategy according to the insight they extract from different data sources, no matter if that information comes from structured or unstructured data. The important thing is to come to better conclusions.
For this reason, digital transformation imposes the need to establish a data analysis strategy. Having a plan optimizes costs, increases revenue, and helps you to achieve your business goals.
In this blog post, we will give you 6 tips to create an effective data analysis strategy in your company.
- Use the business goals to make decisions.
A focused organization should have a vision of where the business is going. In a data-driven company, that vision will be more transparent with clearly defined targets and metrics.
Once you were defined KPI’s and associated definitions, you will know what kind of actions and assets you should take to pursue your objectives.
- Don’t trust your gut feelings.
Our intuition relies on an unconscious selection of data points, and some of them are wrong. We incorporate facts and create mental representations all the time. If new evidence opposes those facts, we are very reluctant to rethink our values or recognize new data.
Therefore, our decision-making process is affected by other external and internal factors. We don’t always address issues objectively. Because of this, we end up making illogical decisions.
For this reason, you should compare what you think to what the data are saying. Don’t be afraid of change your mind or admit that your first thoughts were wrong.
- Bring the data across the organization
In a data analysis strategy, every individual intervenes to achieve business goals.
How to do it?
The first thing you must do is defining general objectives. Then, assign to each department in the company a goal to achieve. Do the same at all levels of the organization until you reach every single individual.
The consequence will be that every person involved will work to pursue his goal, and, by doing this, people will be contributing to the company’s success.
- Collect your company’s data.
When you’re planning your data analysis strategy, you should have a data set. To begin with, forget about external sources. Instead, focus on customer touchpoints with your brand.
- Website visitors.
- Social network analytics.
- Marketing metrics.
- Shopping history.
- Contact interactions.
Sometimes, different teams manage this data. However, if you want to maximize the potential of your organization, you should unify the information you have.
Imagine that you want to launch a new product. Instead of doing risky business, your company opts to analyze your customer’s profile and build predictive models to evaluate how people will react to that product. In this case, due to integrated data, you can conclude and make a better decision for your company.
- Train your team
Not only analysts need the training to examine the data. Directors, sales staff or decision-makers must also have basic analytical knowledge.
Therefore, a comprehensive data analysis strategy covers the training of teams in various fields: experimental design, critical thinking, reporting, statistical analysis tools, etc.
This does not mean that a director or a salesperson must be experts in collecting, filtering, processing or technically adding the data, but they must have a basic knowledge of the terminology, the metrics and even of the interpretations or implications for the business.
Obviously, not all organizations have the budget to create a large-scale training program. However, there are free tools that help in this process: EdX, Coursera, Udacity, Khan Academy or platforms of this type offer online courses to train in various subjects, from introduction to data analysis to machine learning models.
Choose one of these courses according to the profile of your employees and build a training plan that covers the entire company. The key is to start with the basics and then scale according to the needs of your company. What matters is to develop analytical skills and make people feel comfortable with data.
- Select your tools strategically
A common mistake in a data analysis strategy is to invest in tools that the business does not need.
Some companies focus on computing and storage capabilities but do not consider elastic and flexible solutions, such as those offered in the cloud. With cloud computing, you can interact in a multi-cloud environment that interconnects with other areas of information.
Thunder, for example, is a cloud solution that gives you control, flexibility, and scalability that a data analysis strategy requires. In addition, you can integrate it into other clouds to complete the data analysis strategy that your company needs.
Learn in-depth how Thunder works by downloading the following infographic with the detail of all its features. Download it for free by clicking below.