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The food and beverage and FMCG (Fast-Moving Consumer Goods) industries remain cornerstones of the Italian economy, even at the end of this pandemic year.

However, the characteristics of the sector and the Italy’s business fabric reveal a few critical issues and a scant data driven culture, once more highlighting its technological lag compared to its European cousins and the international market.

Business Intelligence as a lever for digital transformation

Net results of the last few years speak loud and clear; the good news is that there is considerable room for improvement for Italian businesses in the food and beverage industry. In particular, it is worth mentioning new and higher performance solutions, capable of responding to the increasingly specific requirements of each company, especially in the area of food management.

According to a survey conducted by the Smart Agrifood Observatory on 288 agricultural businesses, management software tops the list of preferences of 4.0 technological solutions (66%), followed by crop and land mapping systems (40%), monitoring tools for farming machinery (39%) and decision-making support systems (31%). The journey towards digital transformation is still long and probably linked to the main barrier: a lack of interoperability between enterprise systems, coupled with a shortage of skills.

This is why professional figures like the business intelligence consultant and business intelligence analyst, are fundamental for building a Data Driven strategy, which enables companies to satisfy their customers in the best possible way and consequently, to sharpen their competitive edge on the market.

As a technical problem, interoperability can be easily managed by assigning a competent team to the project. The added value by a consultancy firm having an extensive project management experience in the food and beverage industry is closely related to the results obtained.

The reliability and experience of the Atlantic Technologies’ consultants enables the development of comprehensive business intelligence projects. The main prerequisite lies in the quality of data entered in the system, which is why business intelligence software alone is not enough: the technical support of analysts is essential, as they reflect on how to generate useful data and not just on how to present indications deriving from the analysis of available data.

 

Business Intelligence: what exactly is it and why a data driven culture is essential in the food and beverage industry

BI provides an aggregate vision of company information, by measuring data organised according to metrics and defined KPIs. Until a few years ago, business intelligence boiled down to the simple process of data collection and analysis. Today, the integration of technologies and models like Machine Learning and Artificial Intelligence guarantees faster and more precise analyses, calculating the enormous mass of data currently available to the company.

(Read the article: Difference between Business Analytics and Business Intelligence).

In the fast-moving consumer goods or more specifically, food and beverage industries, business intelligence is proving to be an indispensable tool, as it enables management to generate reliable forecasts and optimally assess new opportunities. For this sector in particular, the need to ride the wave, by keeping a finger on the pulse of consumer purchase trends and monitoring the market, is fundamental for boosting the success of one’s own business.

Merely acquiring business intelligence software platforms just won’t cut it: designing a new and fully representative data collection strategy is fundamental.
Specific ready-to-use business intelligence solutions, like the module designed by the Atlantic BI team on the Modern BI Tableau software platform, food and beverage companies can organise and analyse Sell out data.In particular, BI Tableau software module offers the following possibilities:

● Organise data from different sources (Excel, SAP, Salesforce, Oracle, E-commerce)
Share analyses with relevant teams
● Consult an intuitive interface and make aware business decisions
● Benefit from ad hoc analysis for the specific industry.
● Consult data autonomously  Self-Service BI (lightening the load for the IT department)
● Add filters or customised elements
Manage desired commercial fields (sales teams and respective area managers)
● Carry out analyses (Retail analytics) to monitor trends of single products distributed to retail customers
● Accelerating BI&Analytics processes

Moreover, business intelligence solutions are further customisable so as to fully respond to customer requirements.

The role of Data Visualization in Business Intelligence analysis

In addition to improving internal and external company processes, business intelligence must also be a tool capable of rapidly responding to new requests, to guarantee the spearheading of targets. All this can only ever happen thanks to correct data visualization.

In general discussions on data, and big data analytics or data analytics for business in particular, also refer to the sphere of data visualization.
The latter is merely the tip of the iceberg of analyses that can be conducted, while in most cases it is actually the single most important one for decision-makers, insofar as it makes all underlying information understandable and easy to use.

The Tableau data visualization solution enables the creation of intuitive dashboards to explain complex scenarios and analyses, concretely transforming even the most traditional data into information for business-focused users.

Therefore, when BI has the capacity to provide data where it is needed, when it is needed, and fluidly integrates in company processes, data visualization enables communication and helps managers to gain an immediate understanding of relevant aspects, based on the business objectives of the analysis.

Structured approaches and traditional analyses no longer respond to the requirements of companies in a sector experiencing such intense evolution.

New business rules must be coherent, with a strategy focused on increasingly integrating innovation and digitalisation within production processes.

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