Business process automation initiatives built and maintained on the cloud can enable enterprises to have the best of both technologies and drive higher organizational productivity and efficiency.
Supply chain automation management is one of the most crucial operational functions of a business, and one which is significantly prone to inefficient and costly practices. In the pre-IT or digitization age, supply chain management usually followed a definite cycle where management teams would navigate everyday business challenges without any visibility on individual processes within the value chain. The only data they had to work with were annual or quarterly financial accounts or reports, which they would refer, only to fall back on common methods of reducing supply chain management costs without real visibility into broken processes or what caused them. Some of these methods would often include:
- Establishing low-cost manufacturing plants at remote locations from the city
- Hiring and integrating local suppliers
- Reducing manufacturing overheads by turning suppliers into partners
These practices, although highly effective, are nearly not enough in today’s supply chain ecosystem.
Technology has played a crucial role in achieving maximum efficiency in supply chain management with tools like the Internet of Things, artificial intelligence, etc. Thanks to it, we can now keep a record, conduct quality control, and observe every shipment right from when it leaves the warehouse till it reaches its destination through GPS tracking. However, the one technology that can make the entire supply chain management even more streamlined and efficient is cloud computing.
Benefits of cloud computing for supply chain Automation management
1. Adapt to volatile business conditions better
Uncertainties and information mismatch are quite common when it comes to supply chain management. And it has become increasingly clear that many businesses are simply not equipped to cope with and innovate rapidly to tackle the tremendous disruptions in the supply chain environment in the absence of digital technology.
Cloud computing helps you keep up with supply chain disruptions with the help of real-time data management and distribution that does not rely on physical servers and infrastructure. With cloud-enabled systems and services, key stakeholders and operatives across the supply chain can gain visibility over processes and take corrective actions immediately.
2. Regulating efficient data flow in volumes
The traditional flow of data systems does not fully utilize the potential of business information to guide effective, future-proof decision-making. Automation and analytics deployed on the cloud help organizations streamline and maximize the use of internal and external data sources to generate business insights in real-time, and make supply chain management itself a fully data-driven function.
The most effective way to do so is to integrate each individual process for supply chain management, including external partners into the data ecosystem. Supply chain automation systems deployed on the cloud will make each stage of the processes more intelligent, precise, and customizable. At the same time, data analytics can enable faster analysis of the huge volume of data generated during these processes, and make it available to the business leaders so they can make the right decisions at the right time.
3. Industrial-grade digital technologies for heavy data processing requirements
Cloud-based supply chain automation systems can power seamless workflows capable of processing huge volumes of data in a short time, which makes them especially useful for large-scale manufacturing businesses. More importantly, a strong digital or cloud infrastructure for manufacturing will enable businesses to facilitate human-machine integration and processing data from various sources to optimize the entire procedure in real-time.
Cloud computing gives you every possible advantage that you get from a digital platform with added flexibility, and product/services customizations on a mass level. Adding data analytics to the equation will add further credibility to the entire system and makes supply chain automation smart enough to predict uncertainties in the market to keep you one step ahead of the competition.
4. Deploying data analytics with supply chain automation on the cloud
The core purpose of a data management system is to achieve deep business value by utilizing advanced analytics for predictive and prescriptive insights from business data. In the last few years, we’ve seen the prominence of private or public cloud deployment in business operations to create a robust and collaborative digital work platform.
Cloud computing and data analytics are complementary technologies capable of driving greater organizational productivity and more effective decision-making. When used together, it can process the data all across the organization at lightning speed, deploy the right executions at the right time, and virtually automate a plethora of business processes so that the leadership team can focus on more important organizational roles.
However, deploying analytics in cloud supply chain automation needs careful analysis of your organization to know what level of customization your business needs. For example, supply chain automation for big organizations like pharmaceuticals and FMCG requires a thorough understanding of the organizational structure, intricate communication between various departments, a huge amount of data flow throughout the organization with utmost precision, and 24/7 monitoring of transportation with merits to judge the quality of product getting transported.
Before getting started with deploying data analytics automation on the cloud, you must understand the operational and scalability needs of your company. However, you can make this process even easier by partnering with competent third-party cloud automation and analytics service provider like VBeyond Digital.
With that being said, here is a step-by-step roadmap on deploying data analytics in your supply chain automation for efficient workflow.
The roadmap for effectively deploying data analytics on the cloud
Step 1: Create a business case for data analytics on the cloud
Before getting started with deploying data analytics in supply chain automation, it is important to create a business case for it. Firstly, then, businesses need to take into account the following key considerations:
- Strategic business drivers
- Principal applications
- Risk/cost analysis
- Cloud advantage
Planning for these aspects in advance will ensure that your analytics and automation deployments on the cloud are customized according to core functions and information flow.
Next, creating a strong business case for data analytics requires aligning the needs of stakeholders. Specifying the needs of the supply chain management team and IT stakeholders is crucial for building a perfect analytics ecosystem. Additionally, make sure that your business case highlights the value of incorporating data analytics in supply chain automation while communicating with stakeholders.
Step 2: Assess the cloud computing workload
While creating and evaluating a business case for data analytics, it is important to take into account your current workload capacity, the occurrence of unexpected application workloads, and future estimates on workloads to help plan the IT infrastructure around them. This is especially important in the case of supply chain automation, wherein handling unexpected workloads is an important necessity to plug gaps in real time, maintain process efficiency, and ensure customer success.
The effectiveness of the data analytics system in supporting supply chain automation can be evaluated on the following principal functionalities:
- Data storage: Efficient supply chain automation systems need to be empowered with a strong data analytics ecosystem with a highly scalable and low-cost cloud storage system. This is crucial for archiving, governance, and replication, as well as for discovering, acquiring, aggregating, and governing multi-structured content further strengthened by the high capacity storage area network architecture.
- Data processing: An ideal data analytics solution should support parallel execution of the massive amount of complex data processing, connectivity to the enterprise data warehouse, business insights, and online analytical processing. Advanced data analytics also enables you to process queries, calculations, data loading, and data integration to make supply chain automation even smarter.
- Data development: Apart from data storage and processing, ideal analytics for supply chain automation should also involve modeling, mining, exploration, and analysis of deep data sets. Your data analytics solutions should, therefore, be capable of studying past supply chain data and predict future processes and bottlenecks within them to rectify them in time.
Step 3: Develop a technical approach
Supply chain automation and data analytics are perhaps the most technical operations in a business. It is highly recommended to perform a comprehensive technical assessment of existing and planned big data analytics applications and workloads to determine which can and should be deployed to the chosen cloud service. Understanding the current data analytics needs to select the right data platforms and system to operate the entire supply chain management effectively requires a holistic and technical approach.
Step 4: Addressing security, governance, privacy, risk, and accountability concerns
Data analytics is among the most challenging and complex departments to control effectively. It is the unified business resource catering to multiple business operations, it can be the most vulnerable department of your business which requires iron-clad security at all times.
Data analytics governance can be done by the technological experts in your organizations or third-party tech partners like VBeyond Digital, who also ensure that your data stays secure, predict the potential risk to the system, and preventing it at the right time, commitment to protect data privacy, and upholding the accountability of the quality of data generated.
Automation and analytics translate to better-aligned business processes
Deploying business process automation and data analytics on the cloud to power key business functions such as supply chain management, logistics, and production management is key to maximizing business efficiency, optimizing costs, and preventing the wastage of important resources.
VBeyond Digital is a trusted service provider, offering enterprises consulting on strategy regarding cloud, automation, and analytics. We support you from the very early stage of building a cloud and automation strategy fit for your business needs, and also help you with the deployment, maintenance, support, and training required to help your business successfully move to your automation and cloud-enabled infrastructure.
For more information and answers, feel free to contact us.