How to make business decisions not not only quickly, but also accurately?

In business you have to constantly make decisions - from how many metres of of fabric to order, to when to slow down the train to reduce wear and tear on parts and reduce potential repair costs. This used to be done on the basis of hunch, instinct, tradition or assumptions. Today, one relies on data.

Data-driven decision making is attracting a lot of interest in the business world, as well as in the fields of education, healthcare and politics. However, the success of this method depends on both the quality of the data collected and the the way they are sifted and transformed into useful information.

Until recently, DDDM has been the domain of large companies and governmental entities that had correspondingly large budgets at their disposal. Today, thanks to the development of modern IT systems , companies and organizations of all sizes can base their decision-making process on data and thus effectively optimize a wide variety of processes.

The biggest challenges in data management

The classical approach to analytics makes it very expensive. Most time is spent on data preparation, and the analytical part, which represents the greatest value for the business user, is often delivered with considerable delay.

This is why so much emphasis is now being placed on changing this approach. There are already solutions that can radically shorten the whole process. Today's analytical engines analytical engines make it possible to drill down into billions of lines in under a second, and data is delivered instantly. The most important thing is that the decision-makers are provided with already processed data, ready for interpretation, which does not leaving no room for guesswork and providing real support in the decision-making process.

What answers can properly processed data provide?

Based on the data, customer behaviour can be analysed, the effectiveness of the effectiveness of marketing and sales activities, the efficiency of individual teams... The possibilities are almost limitless.

For example, by combining data from different sources, we can:

• determine the likelihood that a given customer will abandon our services;
• assess the effectiveness of marketing campaigns and optimise them with the support of analytics
• maximise the return on investment of a marketing campaign;
• identify which marketing campaigns and messages generate the highest number of qualified leads, opportunities and sales;
• identify the highest conversion rates between each stage of the purchase cycle;
• discover the most important indicators of customer churn;
• increase the conversion rate and speed in the sales funnel;
• measure and monitor standard KPIs in the sales funnel;
• quickly compare current statistics with archived periods;
• identify which stages of the sales cycle are leading indicators of closing transactions;
• check that the rate of sales is increasing in line with the strategic objectives;
• increase speed and productivity by analysing sales performance;
• compare current deal statistics and sales rep performance with previous periods (year-on-year, quarter-on-quarter, month-on-month);
• identify the most effective sales reps;
• identify deals that have slipped to the next quarter or have been
• identify deals that have been put on hold indefinitely.

Properly selected and configured analytical tools can provide answers to many complex business problems and thus facilitate the managing the organization so that its efficiency increases.

Summary

To answer the question posed in the title of this article, in order to make decisions quickly and accurately, they must be based on properly collected and processed data, that give us clear information and clear answers. When choosing an analytical tool, it is a good idea to choose a tool that allows you to analyze, report and share your dashboard views across the organization to monitor performance in real time and continuously improve the real-time and continuously improve ROI with self-service analytics - regardless of IT department involvement.

According to Harvard Business Review, less than 50% of the structured data of the average company is used in decision-making - this shows how much potential there is still to be realized in this area.

And how does your organization use the data it collects? Does it provide real support in the decision-making process? Or does an excess of data and the inability to draw clear conclusions conclusions create nervousness and additional frustration? Let's talk about it in the comments.