As more and more organizations improve in efficient use of data and analytics, their role is no longer just temporary or marginal, on the contrary, it becomes important and crucial in all other decision-making steps. Consequently, most companies find out that on acquired or generated data is becoming dependent, and their value has become so significant that they can become one of the critical assets of a Data-driven organization (DDO).
Effects of transition to DDO
Change into data-driven organization brings several key benefits to why each company should consider such a transformation:
> Revenue growth. Predictive analysis allows for more accurate customer targeting and revenue impact calculation of different pricing scenarios with a faster response to market development.
> Increased customer loyalty. Searching for motivators in customer behavior leads to discovery of their hidden needs and makes it possible to set bids on products to best suit their needs.
> Higher efficiency. It's now possible to isolate and quantify key factors most influencing cost or effectiveness level. This allows managers to make second decisions by issuing recommendations based on available data in real time.
> Reduce risks and operational losses. It's possible to predict situations and risks before they happen, e.g. with sufficient advance, it's possible to predict possible departure of customer so retention activities can be planned to maintain it.
Data analysis situation a trends
What are development and expected trends in companies that actively use both internal and external data?
> Company-wide use. Data usage and analysis is fully reflected in organization's routine operations, integrated into individual applications and provide support for thousands of individual decisions.
> Looking from the future. Strategic role of data and analytics moves from reporting and exploring past results to analyzes and predictions of future developments.
> A new kind of professionals. Team of experts specializing in data analysis is constantly expanding with other talents among whom are already those who understand both commercial and technical issues.
> Availability of tools. A basic component for data analysis - proven and accessible data sources, standardized analytics tools, analytical models / techniques - for all levels of decision making and virtually any internal use are available.
> Easy access to results. Processed data are verified and data resources centralized, describing "a single version of reality" and being accessible to both management and employees for further analysis, decision making, or reporting.
> Centralized data management. Data becomes a strategic asset of an organization with formalized procedures for its processing and responsibilities to preserve its accuracy, predictability and availability.
> Comparative measurement. Data analyzes have a significant impact on business as they allow for continuous measurement of development of key performance indicators (KPIs).
Web analysis applications and systems
By analyzing web applications and systems, we determine quality of web applications and customer systems, possibilities and ways of using them and links to their surroundings. Analyzes are conducted in several ways such as heuristic analysis, focus group, user testing, questionnaire survey or using selected statistical methods.
As a rule, web application and system analytics results are documents that summarize lessons learned from their functionality, their strengths and weaknesses, as well as suggestions for corrective actions. Our recommendations include suggestions for solutions to discovered problems, inconsistencies or missing parts.
Risks of transition to DDO
Change into data-driven organization brings several key risks to why each company should consider such a transformation:
> Scattered and disparate projects. Data skills and data analytics are often scattered across different parts of an organization with little consistency or interdependence and consolidation is often difficult due to unclear or conflicting internal responsibilities.
> Missing competencies. Most companies never had people with the right competencies or skills in data analysis and it never even considered it as a priority. In addition, offer of educated and trained engineers and scientists in the area of data analytics is quite limited.
> Incorrect handling. Data quality suffers when it is not properly managed. Many companies have inherently inconsistent or incomplete data, use disparate structures and manual data processing that prevent better scalability.
> Fear of failure. Only few companies support or reward experimentation. IT is endeavoring to make systems work, but analysts spend more time preparing reports than actually preparing arguments to make decisions about critical IT issues. But working with data requires a creative environment and proactivity.
> Disparity of IT infrastructure. IT systems and software platforms of many companies grew randomly and unmanageably, turning into unusable heap data with data stored in disparate databases or formats.
> New holistic architecture. Designing a new generation of architecture to get right and trusted data, cleaning and processing is a demanding and responsible work. Huge volumes of data represent a new technical problem and become a new risk of cybersecurity.
Way to success for DDO
Way for a company to become a DDO can be challenging. Organizations are often excited about data they have obtained and their analysis in relation to project, but the enthusiasm usually quickly expires and once project ends, it returns back to original procedures.
In other cases, organizations are struggling to deal with this big problem and are not discouraged even when it sees no tangible effect. However, the initial enthusiasm disappears, and effort decreases as resources are shifted to competitive projects.
Key to success is to remain patient and disciplined and to endure an exhausting yet fruitful way for your company to become a Data-driven organization (DDO).