Data challenges at supply chain departments
Supply chain organizations are moved by data. They also can die by not using it correctly. Organizations have to deal with expensive and outdated solutions, built to only support limited data, like sales, purchases and shipping.
Modern organizations need flexibility to integrate and execute analytics including data from different departments, like sales and client behavior. These limitations hold innovation back in supply chain departments, forcing them to maintain outdated processes, which in turn decrease efficiency over time.
Problems when using different solutions
As the amount of information you receive increases exponentially, modern and innovative uses for it surface within your organization. However, established solutions are complex, expensive and outdated. Organizations are forced to make due with what they can afford and some departments end up being closed inside their own data silo.
When you seek existing analytics solutions, you get disappointed by how much they cost to deploy and maintain. You also need to integrate many separate tools so you can centralize, explore and visualize data. This means that if a department is left out of the main data initiative, not only it suffers by not receiving cross-company data and being able to innovate, but the rest of the organization suffers by not being able to leverage this department’s data efforts.
How SlicingDice supports supply chain departments
Your data-driven strategy doesn’t have to be over because traditional solutions can’t help you. The All-in-One Data Warehouse by SlicingDice unveils a new and easy way of really getting the most out of your data. It offers, in a single platform, built-in tools for data integration, exploration, visualization and intelligence, in a very cost effective manner that can be implementable in days. So you save time and money by avoiding expensive and complex integrations among multiple different solutions, costing a tenth of the market price.
This means organizations can leverage their data as a single, complete unit. Every department can contribute and leverage other departments’ contributions. For supply chain team, this means being able to get faster insights on how resources are being consumed organization-wide. This also means this team has everything it needs to employ predictive analytics, with our machine learning model. Being able to predict with precision where resources will be needed can heavily impact on costs, by optimizing purchases and supply where adequate.
Schema and data type flexibility.
Store time series, non-time series and geoposition data in the same database. Store data with different structures. Query as you need.
Real time streaming and visualization.
Stream data and analyze it in real time. Perform queries and see dashboards updated as fast as you need, so so action can be instantaneous.
Improve efficiency with advanced analytics.
Predict maintenance, best routes and even future demand with our machine learning module. Refine predictive model with constant use.
Don’t worry about integration, maintenance, backups, sharding, partitioning or any configuration. Focus on logistics and operation.