Business Intelligence

The key to profitable business: data-based decision-making

Gregor Alaküla
Grant Thornton Baltic saade Kasvukursil Äripäeva raadios

Running a business in the most profitable manner possible takes smart decisions. Data – and including data in the decision-making process – are an inseparable part of this, panellists on the Äripäev radio programme “Kasvukursil” said.

“To manage activities and expenses, budgets are usually quite detailed so that expenses could be divided among different activities and products. In addition, managerial accounting with data for specific business areas are brought to executives to allow them to make as informed a decision as possible,” said accounting expert Kaido Vetevoog regarding budgeting.

Vetevoog said the most important thing when it comes to preparing a budget is that forecasts should be realistic. That is also important for making promises to customers. “It is natural for customers to want to get everything quickly and cheaply and in a competitive situation it’s natural to want to make expansive promises. But of course, customers also care about promises being kept,” he said. Data-based decision-making helps to avoid making false promises.

Grant Thornton Baltic’s IT solutions expert Vladimir Rüntü said that the decision-making process often requires comprehensive data sets and a bigger picture. To assemble the bigger picture, data on the company should be gathered and stored in a common data warehouse separately from various apps and programs. “Once the data are in one place, they can be used to rapidly generate connections, at the necessary level of detail, since data in warehouses is generally also systematized.”

Helps stay competitive

Replacing intuition with data-based decision-making also helps companies stay competitive. For example, smart decisions have to be made in a situation where the input prices of production increase for a company. “Often a company will have to decide whether to optimize quantities or find cheaper input. The company has to respond to the change immediately because that is the only way to still make the result forecasted for the year,” said Vetevoog.

Another example: analytics also provides a tip-off when a customer is about to leave a company. “Then the customer can be called and asked about the reasons for leaving, what is wrong with the service and why they aren’t satisfied,” said Rüntü. “Data analysis also helps identify loss-making clients that should be allowed to leave.”

The data can also be used to determine the efficiency of the employees and machinery. “For example, how much work a given person or machine did,” said Vetevoog. “Then it can be decided whether any machines require additional maintenance,” he said.

Analytics should also be efficient

In parallel, data analysis should be kept from becoming too energy intensive. “If most of an analyst’s time is spent entering data with no time left over for analysis, it is time to change something for the better,” said Rüntü. Rüntü said that at some point, the volume of data makes number-crunching too complex for an ordinary productivity software like Excel; in such a case, alternative analytics software should be considered.

Rüntü mentioned Microsoft’s Power Bid as an alternative, also Qlikview, which allows data to be visualized better. It is also important to automate data analysis as much as possible. “That cancels out the human factor and risk of human error. Data flow becomes more stable and structured,” explained Rüntu.

Organized data make decision-making faster, Vetevoog points out. “Every morning, data can be emailed to management so that they see how the previous day went,” points out the expert. “Information can be managed and any discrepancies can be given immediate attention.”

The average expense of professional analytics for a company is about 100 euros per one user per month. “But needs can vary in different periods and based on that, service plans can be changed to make the expense more reasonable,” said Vetevoog.

A role model for government

With enough data, Vetevoog notes, activity-based budgeting can be used. “The principle is simple. You look at the costs and see what income can be derived from them,” explained Vetevoog. “Expenses are distributed among various initiatives and programmes and later you evaluate whether something is reasonable or not, i.e. whether the hoped-for result was achieved.”

The government has also been using activity-based budgeting since last year. “Ideally it should help the government decide what is reasonable for the state to do itself and what it should outsource to the private sector,” said Vetevoog. “Unfortunately, it is not quite there yet and the practical output leaves something to be desired.” Rüntü noted that given the sizeable volume of data used in the state budget, here, too, the emphasis should be on solutions that allow to communicate them to MPs in electronic form. “It isn’t complicated and it could be done on a sector-by-sector basis, separating education, national defence, and also fields related to state secrets,” concluded the expert.