The recent Magic Quadrant publication by Gartner, regarding platforms for Business Intelligence in 2015, has highlighted the changes that the BI sector is adopting, in order to rapidly implement platforms that can be used both by business users, and by analysts to extract knowledge from the data.
Traditionally, business intelligence has been understood as a set of methodologies, applications and technologies used to transform data into information, and information into knowledge, from structured data generated in different business areas of a company. It may seem that Big Data is meant to serve as a substitute or replace it, but it does not; Big Data (Article in Spanish) is more of a tool that will help to develop better business intelligence procedures to enable the:
- Processing and analysis of volumes of information
- Widening the universe of data to be taken into account when making decisions: innate historic company data (sales, production, marketing, financial information, etc.) is incorporated alongside data from other external sources, such as market trends, competitor information, and preferences or feelings towards a brand, as expressed by customers on social networks.
- Providing an immediate response to the real-time data provided by devices (smartphones, GPS, wearables, etc.) and the interconnection between them.
- Working with complex and heterogeneous data structures: logs, e-mails, conversations, locations, voice, etc.
- Isolation of the physical constraints of storage and processing, in order to make use of scalable and highly available solutions at competitive prices.
The role that Business Intelligence plays is still relevant today: it consists of adding value to the data at our disposal, to accompany the business strategy. Therefore, it is necessary to consider the following aspects:
- Our business strategy must brand the IT strategy
According to a list drawn up by CIO.com, one of the worst mistakes and yet, more common when it comes to Business Intelligence, is to enable technology to dictate the strategy. The result, in these cases, usually includes complicated systems, where the infrastructure quickly becomes obsolete, and has the additional disadvantage of being too rooted to be removed easily. Instead, clear, specific, and well-defined business goals, which encourage technology adoption, should be established. Moreover, business experts and end users should be involved in determining the technology to be used to meet the objectives.
- We use agile development techniques
Agile software development is a model that emphasizes iteration and incremental development. The main advantage of this type of development is that it provides organizations with the opportunity to evaluate how far a project has come, and where it is going. Creating, testing and deploying BI technology with quick and adaptable methods enables the incorporation of new requirements into projects on the fly, and this is key when it comes to analyzing information in real-time and rapidly changing environments.
- We do not lose sight of the usability of solutions
Often, there is a tendency to invest in new technology that promises to do everything, with many features that prioritizes solutions to complex problems more over usability. These decisions can end up hurting more than helping. If BI solutions are not intuitive, easy to use and do not mix well in the workflow of the end user, they will most likely not succeed.
- We should turn the numbers and data into a narrative
Data is penetrating all areas of work and the end users need to feel comfortable when it comes to understanding and interpreting the information. It is therefore important for organizations to offer analyses and reports that are easy to understand, tell compelling stories, and are not too complicated to interpret.
- We centralize and guarantee the quality of the data
Having a centralized data repository, which gathers and combines multiple sources; contains the ontology and taxonomy of data; and which will allow us to sort, filter, and obtain information, is essential for the development of advanced analytics, for tracing patterns, and for the application of predictive models or the identification of correlations and future trends.
Another key factor is to ensure the quality of data. Results checks have to be exhaustive, and any difference or error can compromise the users’ confidence in the data obtained; therefore, it is necessary to implement controls to prevent the proliferation of invalid data, to develop processes that improve data quality, and to implement quality standards for cleaning and auditing data.
- We implant a corporate culture that integrates information across the board
In the development of any new project, the collection and traceability of data must be one of the main requirements, as well as the ability to analyze the information from the implementation.
Business objectives must have associated indicators and benchmarks for determining whether they have been achieved.
- We facilitate access to information
Employees must be able to access information regarding their activities and the company’s, in order to gain a better understanding of the strengths and weaknesses; this will also aid them in knowing where the company is positioned and what sort of distance remains in achieving the set objectives. This capability must be supported by specific training in the interpretation of the data, as well as knowledge of the methods needed to analyze and act accordingly.
It is also important to note that the data should not be used to point fingers when failures are detected. If these are shared to analyze causes and establish new actions that help foster development, employees will be less afraid to take risks and will make use of the information for development.
In the era of Big Data, companies that do not adopt an approach based on information, and react at the same speed at which the data arrives, will run the risk of being completely out of place. At Territorio creativo, we are committed to a strategy which prioritizes the collection and analysis of information so as not to leave out key assets: leveraging information to better understand our clients (Article in Spanish), develop new products or services, and maximize efficiency and internal productivity.