The world is racing toward digital transformation and cloud adoption. To stay relevant, competitive, and agile in the market, it is essential that retail energy providers transform their digital landscape and be aware of cloud capabilities. Whereas legacy systems were hard to set up and maintain, technological evolution has made setup easy even for complex solutions. Digital transformation can solve common problems that legacy retail energy systems have.
Some of the high-level advantages of digital transformation and cloud adaption:
Traditional systems cannot handle large usage data sets at times. Due to this limitation, it is difficult to perform analytics and derive business usable metrics. The root causes of most of these limitations are typically tied to the volume of data and how it is stored: Usage data can be captured in different intervals (monthly, daily, hourly, 15 mins, etc..). Over time, the amount of data being stored can be huge. This size puts tremendous stress on legacy servers, computing, and memory that must be continuously evaluated and increased appropriately which is time-consuming and expensive. Also, a traditional analytics design may run into performance and scaling issues. In a cloud environment, computing and storage are readily available and can be quickly configured based on business needs. Clients do not need resources to maintain servers and required upgrades, instead, they can focus on core business. Cloud environments can easily handle huge data sets with minimal development efforts.
In a traditional setup, data will be profiled, cleansed, transformed, combined, and loaded into a data analytics system. Retail businesses have multiple applications like CRM, billing, load forecasting, financial accounting systems, etc. To get the consolidated reporting that contains information from all these systems in a centralized location, data must be combined and put into a data analytics platform. This typically causes performance issues. Using the cloud, source data from different applications can be dumped into a landing zone (data lake) and an ETL or ELT process can be built on top of the data lake to get the transformed data into the analytics system (Azure Synapse, AWS RedShift, etc.). Cloud systems can handle structured, unstructured, and semi-structured data. These systems can be scaled up or scaled down seamlessly or can use a server less setup to handle huge datasets automatically as they grow over time.
Cloud environments provide workflow designer and components (Azure Functions, Azure Logic Apps, AWS Lambda, AWS Step Functions) to define the business processes quickly. Most of the components provide standard functionality to accomplish steps in business processes and provide the ability to extend functionality. Retail energy providers can utilize these capabilities to quickly define and implement business processes.
When new applications are being developed, different environments are required to be set up for development, testing, UAT, and production. In a traditional environment, it is a time-consuming process and requires more resources to set up and maintain this infrastructure. Whereas in the cloud, it is quick and easy to create environments using reusable templates and is more cost-effective than a non-cloud-based architecture. As soon as dev and testing are done, the resources can be freed up.
All in one place
Modern cloud architecture provides robust reporting and data utilization capabilities in one place that include custom applications, source data, data dictionaries, reporting, and machine learning models. It provides more security and a one-stop shop for all business needs. It also gives the ability to easily connect to other applications using modern technologies (Azure API management, Azure Event Grid, Amazon API Gateway, Amazon Event Bridge, etc.). Cloud environments provide tools to monitor the health of the systems, infrastructure, network, and utilization costs (Azure Monitor, Amazon CloudWatch)
Real-time data can easily be collected and curated to consume using streaming technologies (Apache Kafka, Apache Spark, Azure Event Hubs, Azure Stream Analytics, Amazon Kinesis, etc.). Usage data can be collected in real-time using streaming tools and generate analytics quickly to provide usage patterns to the customers in near real-time.
In a cloud setup, infrastructure, servers, computation, and tools are readily available for use. Everything is one click away. New business cases can be developed and tested rapidly with predictable costs. Retail energy providers can use these capabilities to try proof of concepts for new products, new markets, and new offerings to the customers.
Machine learning models
Cloud environments provide an ability to define, train, and run machine learning models (Azure ML Studio, Amazon SageMaker). Retail energy providers can use these models to run descriptive and diagnostic analytics to analyze historical metrics like usage, supply, and demand patterns. It is also possible to run predictive and prescriptive analytics to forecast future business needs based on different factors, like usage, weather, demand, supply, etc. Since a company’s data is in one central location (data lake), it is easy to provide the necessary data points to run the machine learning models.
High availability and fault tolerance
Cloud environments can provide high availability with low latency. Retail energy providers can build critical applications, such as customer portals using cloud technologies to provide uninterrupted low latency service to the customers. Also, cloud environments replicate the data to multiple regions/zones that provide fault tolerance and disaster recovery.
Clouds environments are highly secured and provide enhanced data protection with encryption at all transport layers, secure file shares, and communications. Also, they protect against unauthorized use/access, distributed denial of service (DDOS) attacks, hackers, malware, and other risks. For instance, there are rigorous recent requirements in NY1 that must be met after past cybersecurity incidents in the industry. These are potentially going to be much easier to meet using a major cloud provider with many standard protections vs. needing to do it all yourself on-premises.
In conclusion, as technological innovation continues evolving, the need for continuous digital transformation will become even more pressing. Cloud environments provide a vast ecosystem of tools and technologies, and they are cost-effective, innovative, reliable, efficient, scalable, and secure. Cloud adoption gives a quick win to retail businesses of any size in the short and long term. It helps in achieving business goals quickly and staying competitive in the market. This article provides quick insight into cloud capabilities that can be used to accelerate retail energy business goals.