How we can retrieve buried treasures?
We are used to see targeted advertising on the Internet, and no longer surprised that social networks and search engines know our preferences very well. The opportunities behind this are mind-boggling — using the available data to achieve business goals, both high- and low-level.
Low-level - acquiring new customers, increasing the average check, reducing costs. High-level ones include the creation of goods or services, the search for new channels to enter the market, that is, the formation of business models.

Despite this well-known value of data, according to Forrester, "Firms make less than 50% of their decisions based on quantitative information rather than intuition, experience or opinion." The respondents are aware of the problem: 85% want to use analytical data when making decisions.
But how you can approach? 91% report that using data in decision making is challenging. Yes, of course it is difficult. First, you need to understand exactly how to extract valuable information hidden in raw data. There is a good work for the analyst here. Second, processes are not easy to organize - data-driven operations affect people and technology. This affects the core foundation of any organization - its culture. However, companies that are willing to change from the inside out for promising opportunities can ultimately generate significant profits.

The most typical goals for data use initiatives include the following but are not limited to that.

• Understand customer behavior by observing transaction flows, use of products and services.
• Collect information from surveys to understand revenue trends, customer retention, and proactively address retention issues.
• Collecting data at control points of business processes to identify opportunities to improve operational efficiency.
• Detection of fraud.
• Optimization of employee productivity.

What about Data Executive?
Many companies fail when searching ways to bring data to work. The challenge includes not only building a IT infrastructure, but more organizational restructuring, and possibly a complete reboot of the business. It is good practice to appoint a Chief Data Officer and delegate all work and responsibility to him or her.

Who is this person? First of all, the CDO must be a diplomat with great authority. He will have to maintain relationships with all the major leaders within the company and with the data providers. CDO requires, of course, broad technical expertise, but understanding the business is even more important. The data executive also needs to be able to see into the future, so forecasting is another talent that he must have.
So, the data chief is in charge of the hard work, but he gets broad powers to oversee all aspects of the company's operations. CDO reports to the CEO or board of directors. What do they actually expect from our hero is the following.

Delivery of data in real time for quick decision making.

• Predictive and prescriptive models to optimize operational processes.
• Self-service infrastructure to work with data with improved quality and security.

Behind it all, of course, lies technology, from storage to analytics with dashboards, as well as clouds, security, machine learning, artificial intelligence, and more. All of this requires orchestration to continually discover, analyze, and continually use data to generate actionable ideas for business improvement.

How can you measure how far you advanced with all that?
Let's say that you are already purposefully working with data to increase the profitability of your business, and you want to know the return on investment in this process. So it's time to define measurable KPIs and track them continuously.
How many new clients are you getting per month from new practices? How does the average check change? How much money did you save on optimization? How does the total profit change and how is it structured? Are the teams productive? Data processing not only influences all these questions, but also helps to answer.
It is important to track progress over time, so evaluation should become an ongoing part of working with information.

What next?
During the pandemic, organizations that invested in data transformation have achieved tangible results. Markets around the world were volatile, but with the help of effective analytics, many predicted the use of liquidity and surges in transaction volumes to be more sustainable and efficient use of loans. 
This experience helps to understand and recognize the benefits of processing data. We in Softline are fairly experienced with this and I invite you to discuss how we can drill in your data for treasures!