However, this is not a simple process. On the contrary, setting up a correct Business Intelligence system is the result of complex work at a logical and operational level.
Data collection
Business Intelligence, in a certain sense, is the daughter of the large amount of data that companies have available today thanks to the simplicity of collection. We have long sung the praises of Big Data and, in fact, today it is easy to obtain them: any company in fact has at its disposal a large amount of data coming from very different sources.
Limiting ourselves to online systems, even the smallest companies today look at website analytics data, social media data and the results collected by advertising platforms. Often, to this first data we can add all that comes from marketing automation platforms, if present, and/or other tools used. We then move on to the data collected by the company in its relationship with the customer, the First Party Data: the customer and prospect registry, sales data. Interesting data can come from all areas of the company, including accounting or warehouse (think, for example, of data on returns, or shipping times, or the insolvency rate).
The first step of a Business Intelligence system consists in integrating this information. This first step, in practice, is far from being a given within companies; it is not uncommon to encounter problems related to data integration:
Many (companies, but also consultants!) do not care about this integration , considering only separately the reports of the various business areas or the various data collection tools. This is how, for example, Google Analytics is mistaken for a “Business Intelligence system” (when in fact it is a sophisticated data collection system and has some very standardized processing and reporting capabilities, without the completeness and versatility of BI systems).
In more common cases than one might think, one notices a certain reluctance of individual company departments to share operations . As irrational and evidently wrong as it may be, this “data jealousy” is present.
Neglecting data integration means closing off the possibility of identifying connections and trends that should be addressed.
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Data processing
Once the data has been integrated, it will be necessary to process it in order to have effective information as an output to monitor the company's performance and to provide efficient support to the decision-making system. From the raw data we then arrive at a series of different types of indicators: in particular we will have the Lag indicators and the Lead indicators.
Lag Indicators are backward-looking performance indicators, usually expressed in absolute values. For example, last month's turnover.
Lead Indicators are those that identify a trend, such as the relationship between this month's growth and last month's. They are used to monitor the company's current performance and future prospects more closely.
A well-designed Business Intelligence system will allow company management to constantly monitor key indicators, to intervene promptly where necessary and to identify opportunities when necessary.
