Data is increasingly important in today’s market and has become a key piece to guide decision-making and strategic planning for companies across all segments. However, to transform this information into knowledge and competitive advantages, organizations need to prioritize data driven decisions.
This term refers to data-driven organizational processes in which companies base their decision-making and strategic planning on the collection and analysis of information – rather than intuition or anecdotal experience.
These decisions are not just a tool, but a whole methodology that gives organizations a more accurate idea of their business, allowing them to take advantage of opportunities and anticipate trends and problems.
For this to happen, the tools used in data driven companies collect data from different sources, both internal and external. They combine information in order to offer a clearer picture of the market – customers, products, competitors, suppliers and conjuncture – and of the organization itself, so that managers can act accordingly.
Unfortunately, many managers still don’t make their decisions based on data, putting their businesses at risk. One of the challenges when making this kind of decision is dealing with the large amount of data generated every day.
Therefore it is necessary to identify efficient processes for the collection and analysis of information, so that all available knowledge can be strategically used. Several tools can help with this process – and nowadays, you can even find artificial intelligence solutions to automate most activities.
How was this process born?
The concept of Data Driven decisions emerged as an extension of data science, a field of knowledge that uses scientific methods and algorithms to transform data – both structured and unstructured – into knowledge.
In the current corporate environment, this is done using tools such as Big Data, Artificial Intelligence and Machine Learning, to obtain insights from the collection, cross-referencing and interpretation of market data.
The goal is to increase the organization’s competitiveness, leading to improved results.
What are the goals of this type of strategy?
Data driven culture is geared towards making businesses more focused on market demands, with a positioning that considers a greater number of factors. After all, analysis will always be based on indicators including the state of the market and business objectives in the medium and long term.
As a result, intuition is no longer part of a company’s routine, leading to more robust and reliable choices. The ensuing adherence of professionals will result in increased engagement by teams in pursuit of the company’s goals.
For a company to be considered data driven, it first needs to collect data from various sources – like ERP system, CRM, sales and marketing systems, social media, market data and consultancies, etc.
Having implemented a systematic collection process, it is necessary to integrate this data. That is why one of the pillars of data driven management is ensuring collective access to data. In this way, managers always have complete reports at hand, and can consult the company’s database to solve any problem.
5 steps and tools to help you
The first step towards a data driven culture is investing in the right data analysis and management solutions. These solutions are software, tools and methods that enable the collection, storage, processing and interpretation of raw data, and then transforming them into valuable information.
Software such as CRM, BI and Big Data systems can reduce costs and improve the quality of analyses. In addition, they make room for data to be adequately stored and managed by all teams. Here are some steps you can follow in order to make data driven decisions:
1 – Sales analysis: decisions based on data are much more powerful than those based on assumptions. So a good CRM and planning tools are essential – as are OKR templates to guide you and improve the organization of relevant processes.
Team leaders can use these tactics to analyze the information provided, compare reports and, as a result, make informed decisions to drive business growth. Your data will also be more organized, with all teams acting in an integrated manner and avoiding mismatched information.
2 – Social media analysis: data-driven tools play a big part in the world of social networks, helping professionals to find new content, learn about the competition, understand what users are saying about the brand and analyze results.
This data can be used to gauge how to develop creative strategies for each of your company’s channels.
3 – Web analytics: this is the process of measuring, collecting, analyzing and reporting data about users’ browsing and online interactions. In other words, structuring and collecting data to understand how the public behaves in the digital universe.
As consumers around the world generate huge amounts of data at any given time, we need to know how to analyze this information to improve our actions going forward.
4 – Lead capture: in Digital Marketing, lead capture is when companies are contacted by people who are interested in their products or services. This information can be captured as data to assist in future decision-making.
In addition to analyzing all leads from a given period, check whether complementary actions such as paid media, content production, email marketing and others are delivering results.
Doing so will let you identify any errors in your sales funnel, and the relative healthiness of your conversion rates.
5 – Email marketing: this type of content goes beyond simple email, and contains valuable information about potential customers and consumer behavior. Like any good data-driver, marketing automation tools provide data and insights to improve the performance of your strategy.
Find out who is opening your emails, how many people have clicked on email links, and how many of them became customers, among other important metrics.
Data driven decisions are the future of business management. As technology advances, collecting, analyzing and interpreting data to transform it into strategic knowledge means staying one step ahead of competitors who remain resistant to this transformation.
But the path to a data-oriented culture isn’t always a straightforward one: it can mean training all company employees, and hiring qualified professionals to optimize the use of this information and of appropriate tools to make better data driven decisions, increase predictive capacity and provide more autonomy in internal processes.
