Advanced analytics: Real use cases and benefits for companies

Now is the time to bring together all the concepts previously introduced and understand how they can benefit us beyond just a theoretical plan. The possibilities offered by advanced analytics are so extensive that any industry and business model can obtain numerous advantages: from retail or transport, to construction and automotive, to healthcare, pharma or food.

Use cases in advanced analytics. Compilation of scenarios of interest

Below, we present a compilation of cases of interest structured into eight large blocks and applied to a wide variety of industries. They have been selected based on the areas of the greatest business impact and the activities within those areas that advanced analytics can optimise.

Use cases in advanced analytics in supply chain management

• Forecasting demand: using historical data, it is possible to forecast future demand more precisely. This helps reduce excess inventory or avoid product shortages, and can serve customers more efficiently. Advanced analytics models take these predictions to the ultimate level by determining demand by material or material components, customer groups, geographic regions, among other variables. This is not a general model, but they are able to adapt to the specific characteristics of each case.
• Optimisation of the supply chain: we can establish models that identify bottlenecks, determine the efficiency of suppliers and thus optimise transport logistics. This translates into lower costs and greater efficiency throughout the supply process.
• Risk management: analytics also allows us to detect patterns and trends that could indicate future risks, such as the possibility of supply chain disruptions. With this information we can anticipate these risks before they occur while also minimising costs.

At SEIDOR, we recently collaborated with customers working on such solutions. For example, we were involved in a project to forecast demand on portfolios of thousands of unique references, and we were able to get the client to automate all processes up to the generation of results.

Use cases in advanced analytics in maintenance

• Detection of anomalies: models can be created to recognise the normal behaviour of a system and then alert when a deviation occurs. This method is very useful for detecting incidents or malfunctions that are not very frequent and therefore difficult to foresee with historical data.
• Classification of errors: you can go one step further and not only detect the error, but also classify the type based on data patterns. This can help technical staff identify and solve problems with greater efficiency.
• Optimisation of maintenance scheduling: the resulting information also reflects the optimal time to perform preventive maintenance, based on the historical data patterns collected in real time. This can also help prevent possible errors while minimising the downtime of the maintenance team.

Use cases in advanced analytics in industrial processes

• Quality control: thanks to Machine Learning technology, we can identify any type of variation or error in products, which allows early intervention to correct any setback before they become more serious problems. This can improve the quality of product and reduce the costs associated with refunds and claims.

At SEIDOR we have recently collaborated with customers such as Almirall, deploying a cloud automation solution that speeds up quality control processes. In scenarios of this type, companies see reductions of more than 90% in the time taken to conduct checks.

Use cases in advanced analytics in call centres and customer service

• Optimisation of resources: in terms of customer service, we face two challenges: providing an quick response to the customer and knowing the staff we need to provide that response without increasing costs more than necessary. Thanks to advanced analytics, we can, among other things, adjust and optimise staffing for shifts. We also have the full information of our customer: customised recommendation of products and services; incident or order history; potential interest and reason for the call or automatic redirection, for example.

At SEIDOR have recently collaborated with clients such as the emergency service of the Generalitat de Catalunya to optimise their call centres through the aforementioned processes. They have been able to conduct their activity while maintaining their strict service levels.

Use cases in advanced analytics in logistics

• Fleet management: fleet management optimisation is another benefit that advanced analytics models offer. This may include assignment of vehicles to routes, maintenance scheduling and, again, forecasting of possible vehicle performance problems. All this is also necessary to make progress in reducing environmental impact and energy costs
• Fraud detection: it is possible to make models that identify fraud patterns in logistics, such as delivering packages in unusual locations or unexpected changes to delivery routes. Undetectable fraud patterns can even be detected a priori by a human being.

Use cases in advanced analytics in warehouses and physical spaces

• Optimisation of warehouse layout: advanced analytics models can analyse data on sales and product movement patterns within the warehouse. These systems suggest organising products in such a way to minimise unnecessary movements and improve efficiency during collection.
• Dynamic pricing strategies: it is possible to analyse sales, inventory and demand data to help determine optimal pricing strategies and in time for products in the warehouse, according to individual configurations, order types, etc.

At SEIDOR we have worked with customers such as Frit Ravich to make advances in warehouse optimisation using digital twins, which can detect improvements in order delivery times throughout the year's various campaigns.

Use cases in advanced analytics in marketing

• Programmatic advertising: advanced analytics allows models to be generated to make real-time decisions on which ads are ideal to show a potential customer at any given time. Based on a series of factors, such as their online behaviour, location, time of day or the type of device they are using, it is possible to determine the most suitable type and format of advertising.
• Optimisation of ad creativity: it is possible to go one step further and analyse which elements of an ad (combinations of colours, words, images and sounds, etc.) are more effective for each audience segment, allowing us to create more effective personalised experiences.

Use cases in advanced analytics in user experience and virtual assistants

• Customisation of interactions: learning from the individual preferences of users from their past interactions allows virtual assistants to adapt their responses and suggestions to the specific needs and preferences of the user. For example, they are able to focus the conversation on customer preferences by analysing user history across the website.
• Prediction of user needs: attendees can also anticipate what a user may need based on past conversations or interactions. This way, we offer proactive help and suggestions, notably improving the user experience.

Advanced analytics and solutions for advanced analytics offered by SEIDOR

Advanced analytics is becoming a real revolution, especially after the arrival of advanced technologies like natural language models.

We have the opportunity to make the most of data and make informed decisions. However, the incorporation of best practices and reference methodologies is indispensable to ensure success during and after the implementation of this type of tools.

The SEIDOR Data & Analytics team has a team of experts ready to harness these new technologies and cutting-edge solutions and put them at the service of your business. With over 25 years of experience, we have helped over 2,500 clients.

If you want to benefit from the advantages of advanced analytics and have the backing of experts in the field, get in touch today. We will be happy to assist you in making the most of your data and to help your company achieve success in today's competitive business landscape.