S2E creates Big Data Analytics Platform for Hippocrates Holding

S2E creates Big Data Analytics Platform for Hippocrates Holding

Traditionally one of the least dynamic and innovative sectors – the pharmacy sector has been profoundly changed by a 2017 law, which allowed corporations to own private pharmacies and removed the limit of four licenses for an identical company.
In this new business environment, two young entrepreneurs, former financial managers Davide Tavaniello and Rodolfo Guarino launched a startup in 2018 to create an extensive network of pharmacies called Hippocrates Holding.

About Hippocrates Holding

The initiative was extraordinarily successful in terms of funding raised and operational acquisition of pharmacies. In just a few years, Hippocrates Holding became the first independent company in the sector, owning more than 240 pharmacies, mainly in northern and central Italy, with more than 1,000 employees. With the ‘Lafarmacia’ Brand, Hippocrates has a clear and distinctive feature that innovatively combines the traditional pharmacy’s values such as hospitality, quality, and the pharmacist role, a comprehensive consultant, to offer a cutting-edge customer experience.

Technological requirement

Such a project required a ‘zero based’ big data management system to connect the pharmacies in the network, ensuring control, harmonising financial management flows, logistics and analytics to extract valuable data for business intelligence and guide development decisions.

S2E Contribution

And this is where the story of the young startup intersected with that of S2E. Since April 2019, S2E has been providing Business Intelligence and Data Management consulting, and together with Hippocrates, defined the roadmap for the architecture development. This was a complex challenge that required an innovative approach that was as creative and unique as the Group, for the nature of the shops and specificity of the information to be managed and integrated at multiple levels and for different purposes.
S2E Development & Data Management Business Unit Director Stefano Bonfatti said: “Our solid vertical expertise in designing integration architectures and data management business line convinced Hippocrates Holding to engage us on both fronts. In 2019, we accompanied the initial phases for the integration of the first 20 pharmacies. Then, we supported Hippocrates in defining the IT architecture development strategy for the implementation of the main components and systems: ERP, pharmacy management and group logistics platform. We were chosen for the vital task of managing data flows between the systems of the various vendors, with an installation plan that covered 2020 while developing the data warehouse and business intelligence component.”

Challenge

The proposed architecture is aligned with the most modern and innovative best practices while considering project constraints and requirements. It is cloud-native and oriented by design to big data and advanced analytics, an ideal choice given the client’s features and impressive growth speed.
S2E Solution Architect for Big Data and Machine Learning Alessandro Sicoli said: “As for the data warehouse and analytics, we chose the Lake House model, i.e. a big data architecture capable of storing structured and unstructured data and having a high performance for data correlation and analysis. This model has two advantages: Lake House presents itself to third-party systems as an easily integrated data warehouse, while being ready to support intelligent engines based on machine learning algorithms and artificial intelligence.”
Amazon Web Services (AWS) was chosen as the cloud provider, optimal for a startup like Hippocrates because it combines robustness with ease and speed of implementation, and has an incremental cost model that is always in line with business growth.
At the heart of the system is the integration layer between the peripheral systems and the Lake House. Its importance lies in the fact that it integrates the different protocols of the interacting, largely proprietary systems. Thanks to the AWS cloud infrastructure and component design, it is easily expandable and scalable to support larger loads and costs. The ad hoc integration layer interacts with Amazon S3 object storage and Amazon RedShift cloud data warehouse, optimal choices for implementing the ‘Lake House’ component that frees the user from the costs of building and managing an on-premise cluster. As a result, it enables seamless upward scalability and significantly reduces operating and management expenses for the same performance.
Hippocrates Holding CIO Iacopo Iacopini said: “Hippocrates Holding’s project has always had ambitious goals to be balanced with priorities while starting from scratch. In the beginning, our primary need was to make the pharmacy work or make it work better by taking care of the specific features of each acquired pharmacy. We decided to adopt tools that allowed central governance of the growing and important pharmacy network right from the start. Our need is to have the ability to intercept business phenomena within our organisation and analyse them from a managerial, directional, operational and detailed perspective. This was created and developed during extreme growth, up to the current rate of 10 pharmacies per month, with the continuous addition of a volume of data and details and the flexibility required by a business model subject to constant change. Over time, we have diversified our commercial range towards the consumer and strategic objectives, and are convinced that reactivity is a fundamental part of our DNA. We are a chain that makes technology a tangible asset, and analytics is a driving force in our decision-making and operational process.”

Benefits

The defining element of the overall IT architecture is the integration layer, i.e. creating a central feature that sorts information between all systems. This means, for example, that the sales data coming from the pharmacies must be routed to the logistics platform to initiate the product replacement processes and the company ERP for the financial and accounting aspects.
Two approaches could be taken to meet this need. The first consisted of creating two data flows out of the pharmacy management system and directing one to one system and the other to another system, but risking duplication of flows, loss of control, or even misalignment of information. S2E, together with Hippocrates, has decided to implement this central element that allows the pharmacy to send the data only once, for example, transform a receipt and send it simultaneously to the systems interested
in that data. This allows extreme governance of a complex architecture: everything goes from one point through a dashboard where all information flows are monitored. “It means I can effectively fulfil my two roles as a CIO, namely the technology and information management and active support for business processes” Iacopini said. “This infrastructural element, which at first glance seems to be a ‘technical’ element, in reality, allows me to fully satisfy both needs, i.e. the governance of the technological infrastructure and business architecture.”
Another significant aspect of this approach is that it solves the problem related to the extreme heterogeneity and obsolescence of the acquired pharmacies’ IT tools and protocols. Having implemented the various connectors, it is possible to process a file generated by a traditional source and transfer the information content to modern tools

In brief

– A modern and innovative, cloud-native, big data and analytics oriented, by design platform
– Agile design method to respond to rapidly evolving and efficient processes
– Evolved cloud-native integration layer with ad hoc connectors, which is the central element of information collection and distribution between all systems
– Flexible and scalable architecture with a scalable and cost-effective model compared to other solutions
– The time to market of this type of approach potentially reduces implementation times for this type of project by order of magnitude.

Solutions and Platforms

– Amazon S3
– Amazon RedShift
– Amazon DynamoDB
– Amazon Athena
– AWS Lambda
– AWS BAWS Batchatch
– Amazon CloudWatchAmazon CloudWatch
– Amazon QuickSightAmazon QuickSight