Those who want to be successful must know how to accomplish it and in order to do it, they must have adequate information. Where to get it from? The answer is: the Internet, computerization, servers and databases. We have a huge number of them at our disposal. In 2011, the shocking news was that the energy consumption in monstrous Google data centres reached 2.26 billion KWH, i.e. the equivalent that is required by an average size city.
Transactional systems like SAP gather financial, personnel or warehouse data, CRM store information about customers, production systems about production progress, and warehouse management systems about inbound and outbound goods. Each of them is linked to a database where each day more and more rows of information are stored.
For enterprises, data are an additional source of benefits. Better decisions, lower costs, higher revenue, and competitive advantage – this is the business mantra. Appropriate application of information offers a promise of achieving those objectives. Are we able to forge them into business success?
Building the competitive advantage
Analysis of company data requires new tools and skills as well as the appropriate corporate culture. What is more, the ever greater challenge facing the businesses is the utilization of the results of analysis, i.e. implementing them in a systemic manner in various internal processes.
Making analyses requires hiring people with education in statistics and also more and more often in IT. In order to work effectively, they need efficient equipment, software and unlimited access to data, partial freedom in operations and the possibility to present results to the people in the organization who are their preferred recipients. It is a challenge since not always analysts are able to translate analyses into a language understood for other employees.
On the one hand you need people who feel at home in the world of data but understand the world of business at the same time. On the other, in today’s reality everyone must be familiar with the world of numbers and statistics.
Should analysts be spread across various departments? Should they coordinate, exchange experience, or perhaps form one team as an analytical Centre of Excellence? One should realize that the tasks required by the modern analytics are best dealt with by a team and not a single employee.
“Appropriate information for appropriate people” a.k.a. logistics of information is the concept of using data in a company. Sounds easy but in practice it poses a great challenge. With many systems in one company and the same data with different names (e.g. if a customer in one system is called XYZ sp zoo and in another XYZ sp. z o.o., computer programs will treat it as two different companies). An important term in BI is “one version of the truth” or being based on one source of data and on shared definitions. In practice it means building a data warehouse and creating reports. Data warehouses gather data from various systems into one database, and then clean and correct them. On the basis of data processed in this way, reports are created which are designed for specific needs, e.g. the sales department may be interested in the relations between the number of days in a month and the number of orders from customers. Reports are available for instance through a browser or on the Intranet. For several years now Raben Group has been successfully building its data warehouse based on the Oracle technology.
It is one of the most important factors. The possibilities of spreadsheets are insufficient for advanced analyses. They can handle just a limited volume of data. Software for data visualisation is much more useful for communication with business. They are new tools which change the approach to the process of making analyses. They emphasise the visual presentation of data using various charts and appropriately selected colours. They are based on the assumption that our mind has problems with interpreting sequences of numbers but that we are much better at shapes, different sizes and colours. Those tools offer great flexibility in terms of data combination and they use in-memory data processing. They allow for developing dashboards and providing them on a server or through a browser. That is why they are treated as modern BI tools.
The corporate culture will be the data carrier; the propagator of the use and further implementations. The way of managing and taking decisions is important for the ability to absorb the results of analyses.
Data analysis is connected with critical approach to operations – comparing, verifying and drawing conclusions. It is not easy. Is there a place in the company for such criticism? Are employees open for a different point of view being at odds with their intuition and many years of experience? That depends on the corporate culture and the management styles. Effective use of analytics is favoured by the democratic management style and learning organizations where data analysis is one of the sources of knowledge and it encourages people to make experiments and simulations which become a valuable data mine.
Analytics is the world of numbers based on formulas, coefficients, complex transformations and calculations. It is sometimes difficult to grasp at first. Hence it does not have enthusiastic support among contemporary middle and senior managers who are more at ease following their experience and intuition. We are dealing here with a specific generation gap. Current graduates of various studies are much better prepared for working with data. Universities have access to the cutting-edge software and they offer new directions of studies connected with the use of data. In turn, the generation of the current managers is often simply able to remember the times of statistics calculated on a piece of paper and spreadsheets. Before those graduates, already as employees, are promoted to managers and start to have real influence on the way of making decisions, 5 or even 10 years may pass. It should be stressed that it is impossible to effectively use analytics without certain preparation and a positive attitude of the whole organization. The analytics department alone, with supercomputers and experts, is not enough. It is not a building block which we just add to the organization in order to become data-driven. It is a kind of choice of the method running the company.
Analytics can play an important role in building the competitive advantage, which has been presented on the diagram.
It shows several stages which must be accomplished in order to achieve maximum benefits. One must have data of relevant quality. Then use them to build standard reports which is followed by creating such reports by the users - more flexibly and independently. Predictive analytics room for all kinds of statistical modelling and machine learning. When we start using predictive analytics, we will reach optimisation. We will start shaping the reality and not simply react to it.
Choosing to go that way depends on identified applications. On the other hand, without looking at the data, without sifting through them, we will not fully realize what potential they have.
Between sports and business
Statistical revolution also affected sports. At first it was baseball. This change was presented in the Moneyball blockbuster starring Brad Pitt who plays the real character of Billy Beane, the front office executive of Oakland A’s baseball team. Although the film does not show any formula or equation, it was statistics and statistical modelling that were used to select the positions of the players, their influence on victory, as well as the value of an individual player and the whole team. Statistics have replaced intuition and prejudice. Club managers received tools for effective management of the game on the diamond and for making optimal transfers.
Such a revolution is also taking place in football, starting from the Premier League. Football clubs, although they don’t have as huge budgets as many companies, set up analytical departments which employ even dozens of people. They measure performance, valuate players, and forecast their value. They gather statistics on penalty shots scored and defended by individual players and goalkeepers. Milan Lab is an interesting example. Doctors of AC Milan started to gather daily information about the tiredness of the players, the movement of their eyeballs, change of pulse, breath, histories of even smallest injuries, and many others. In this way they optimised the behaviours of players, helped them to avoid injuries in the future and thus extended their careers. Having such knowledge, they also decide about buying new players.
Billy Beane, the coach of Oakland A’s, summarized the use of statistics: “If someone’s decisions are 30% correct and they are able to find out how to increase this effectiveness to 35%, they will develop a 5% advantage which in sport may mean the difference between a victory and a loss.” Is business so much different? ▫