Tesco Stores has obtained a unified, guaranteed IP VPN service for its retail chain stores throughout the entire Central and Eastern European region.CLICK HERE
According to Thomas Davenport, a world authority in data analysis, all companies that achieve success by using business intelligence tools and Big Data have one thing in common. It is an analytical approach towards problem solving and analytics management across the whole enterprise. That means, above all, ensuring wide availability of data and analyses, their effective management as well as enabling collaboration on data analysis to as many employees from various parts of the organization as possible.
Pursuing these goals requires technological excellence, that is implementing platforms that support collaboration between geographically and organizationally dispersed specialists, along with excellent communication skills within teams responsible for the analysis. Both the managers, who shape the organizational structure of a company, and the IT specialists, who implement information exchange systems for employees, have important roles to play here.
State of the art analytical solutions open up new opportunities for every company. However, in order to benefit from them, first you need to deploy new systems properly. How is it done?Read more
Below are a few basic ideas for improving communication inside the company to make it ready for the use of analytical tools:
The more structured the data, the easier it is to draw conclusions based on them. That is why standardizing formats and ways of presentation should constitute a foundation of every analytical solution improvement process. The more coherent the information the company has access to, the easier it will be to integrate the sets with data from the environment that are unstructured and unordered by definition.
Standardization may refer both to technology and to the way the meaning of information is defined (metadata, reference data). Implementing unified formats within this area allows for a much better and common understanding of the available data that can be used by various user groups more effectively, with a reduced incidence of errors and misunderstandings. Data source standardization and ordering is a process all users of analytical solutions go through at some point – from large companies active in various sectors to smaller enterprises interested in a better understanding of the processes that happen in the company and around it.
Every decision is only as good as the information that stands behind it. Therefore, if you want to improve the quality of business analyses and decisions, introduce internal methods of recognition for those who promote skills such as discipline when using sources, constant evaluation of the proposed hypotheses or ability to work on analyses in groups. Without these skills, every company is forced to rely on decisions made on the basis of its managers' or their coworkers' intuition (according to the Guts and Gigabytes survey conducted for PWC by Economist Intelligence Unit, 2014: 30% of global managers make decisions using their intuition, while 28% listen to their coworkers' opinions).
It is a long-known truth that “one image says more than a thousand words.” Changes happening in the business environment under the influence of new technologies, impacting the way information is perceived, make this truth become more up-to-date than ever.
If you want to maximize the number of people involved in information exchange and analysis, you need to make all efforts to keep the process unambiguous and clear. This goal can be easily achieved by introducing a general standard and data visualization tools.
In the world's largest companies, such as General Electric or Procter & Gamble, all employees use the same visualization platform (for the creation of presentations or images used in advertising) with pre-defined templates that are easily customized to various communication needs (source:Thomas H. Davenport, Analytics 3.0).
Modern tools, such as Big Data, give companies a unique opportunity to quickly integrate data collected from various sources, both unstructured and structured. The more varied the sources, the greater the potential value of information acquired as a result of data integration. This is why the champions in using new analytics technologies put so much importance on increasing the number of data sources that fuel internal systems.
Vistula Group, a Polish luxury clothing manufacturer, is an excellent example (source:http://www.businessintelligence.pl/pl/a/Vistula-Group, 26.06.2015). The company constantly processes information related to sales geography, margins, discounts or employee comments in its systems. With the help of IT tools, properly analyzed customer behavior becomes a source of information that can later be used in planning further actions, such as those connected with marketing or sales. By integrating various data sources, the company almost instantly receives information on the most popular patterns or colors, which enables its employees to make up-to-date decisions on the product range available in stores.
Flexible telecommunications architecture is one of the key factors that condition the effectiveness of using analytics in a company. It must provide users with access to reliable, comprehensive and precise information that will help them make the right decisions. This is possible through implementing suitable systems for employees to offer them a direct and instant access to data.
Creating and securing this type of platform is a time-consuming task that requires support from specialized partners who guarantee reliability of all infrastructure elements. Such a process takes years (in case of Amazon.com, it lasted more than a decade). It requires not only designing suitable architecture (that is, an efficient connection between various systems and hardware solutions), but also integrating applications of different structures and operating logic, as well as constant adjustments of the implemented tools as the company's strategy changes.
Effective use of the modern analytics solutions can generate significant savings and contribute to the creation of many new sources of competitive advantage. In order to make it happen, company that uses such solutions must be prepared from the point of view of processes, organization and technology.