Automation and advanced analytics reveals change in customer demand at caring facility, Granhøjen.
Customer Company Size
Mid-size Company
Region
- Europe
Country
- Denmark
Product
- Exasol
- Yellowfin
- Viteco SPEED
Tech Stack
- In-memory analytic database
- BI and analytics products
- ETL programming
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
- Digital Expertise
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Healthcare & Hospitals
- Professional Service
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Predictive Maintenance
- Process Control & Optimization
- Remote Asset Management
Services
- System Integration
- Data Science Services
- Software Design & Engineering Services
About The Customer
Granhøjen is a rehabilitation centre based in Denmark. It has been offering housing, employment and treatment to adults with mental illnesses and social problems for more than 30 years. The facility has created a community where residents have the opportunity to work, get active and learn new skills. Through this process, the residents can create an identity that is not linked to their social problems or illness. They have approximately 120 staff including therapists, psychologists, and interdisciplinary staff who determine the best possible treatment for each individual.
The Challenge
At the privately-owned residences in Holbæk, it is important that the staff, services, and buildings continually adapt to the number of residents and their changing needs. Over time, Granhøjen has expanded from 40 to 120 employees, and as a result getting a complete overview of the company’s key figures has become a heavy administrative task. “The figures we used to give the board were a month old and out of date by the time we presented them,” says Mads Olsen, Chief Operating Officer at Granhøjen, “I felt frustrated that we lacked quick and easy access to information and weren’t able to make management decisions based on up-to-date data. It used to take around 25-30 hours a quarter to collect data via Excel for each board report.” Granhøjen also lacked insight into their residents and the services they required. There was no process in place to understand why residents had been discharged. It was unclear if residents had left because they had gotten better, or whether there was something about Granhøjen’s services they were unhappy with. This knowledge was retained by staff who spoke directly with the municipalities in charge of the residential contracts, but none of this knowledge was captured and used systematically for management information or process improvement.
The Solution
Mads Olsen expected a data project, that would proactively improve the business, to take a couple of years to implement and cost thousands of dollars. However, as soon as he saw Viteco’s solution, SPEED, he knew they could get results quickly, and cost-effectively. SPEED is Viteco’s approach to delivering fast BI projects. It is a fixed price package that combines Exasol - the leading innovative in-memory analytic database technology, Yellowfin - a powerful suite of BI and analytics products, and Viteco’s Data Suite tools and SPEED methodology. Using this combination of tools and accelerators, Viteco are able to deliver a minimum viable product (MVP) within four to six weeks. The team at Granhøjen were excited to get a Proof of Concept (PoC) in motion. Viteco worked with them to extract data from their business applications, load the data to Exasol, and run a workshop to define the reporting requirements before building a set of reports in Yellowfin. With Yellowfin, Viteco have found that you can report at a much earlier stage and do the ETL programming afterwards. The turnaround time for Granhøjen’s management team to extract their first reports was exactly a month and a half. “The consultants at Viteco quickly understood our business and what data I needed to access,” says Mads Olsen. “The price-to-value of Viteco’s BI solution, SPEED, on trial was exceptional. We knew straightaway we wanted to continue with the program. The cost of Yellowfin licenses alone was covered with the purchase of the complete solution, and we’ve saved about 25-30 hours a quarter by automating data collection.”
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.
