Manufacturing companies constantly struggle to integrate innovative techniques into their workflow for enhanced customer service and build trust among potential buyers. One way to succeed in the manufacturing sector is to have a more insights-driven and data-centric approach to real-time information. SAP Analytics Cloud is one such solution to gain crucial business insights on the go.
Why choose SAP Analytics Cloud?
SAP Analytics Cloud is an effective cloud solution designed for enterprise planning and acquiring business intelligence. Analytical tools like SAP Analytics Cloud helps manufacturers to gain raw data and convert it into meaningful and actionable insights. Using this business intelligence data, businesses can focus on more efficient decision-making and boosting productivity.
According to the Apps Run the World, 2020 reports, the business intelligence software market, along with analytics tools, is expected to hit $17.6 billion by 2024. It proves that more and more companies realize the importance of acquiring business intelligence tools for better decision-making and effective planning of their business operations.
Apart from improving performance metrics within an organization, this flexible SAP Analytics Cloud solution makes it easier for the employees to switch between applications seamlessly. It encourages all departments to work with higher efficiency since they will no longer be facing lags in the information flow.
With the integrated SAP Analytics Cloud Planning tools, businesses can make strategic decisions confidently and execute their plans based on real-time insights. The best thing about this SaaS solution is that manufacturers can store all their vital business data securely in one place and access it anywhere, anytime.
How is SAP Analytics Cloud beneficial for Manufacturing Companies?
Organizations using SAP S/4HANA together with SAP Analytics Cloud can handle all the core business areas efficiently, including manufacturing, marketing, finance, HR, sales, and so on. With a futuristic approach towards business planning, companies are focusing on including more advanced technologies that will help them adapt to changes in the upcoming years.
This is why companies are taking digital transformation seriously, and migrating to SAP HANA will ensure that business applications can function seamlessly in the future. According to Statista reports, 17,000 companies subscribed to the SAP S/4HANA ERP system as of the second quarter of this year.
Five reasons why SAP Analytics Cloud is the best solution for manufacturers are:
- It Unifies Data
The most helpful feature in SAP Analytics Cloud is pulling data from multiple sources into one central place. It enables manufacturing companies to access all the required business intelligence data under one roof and eliminates the hassles of dealing with disparate and disorganized data sources.
The primary reason manufacturing departments often experience a slowdown in their workflows is the storage of data in different places. Also, with a cloud solution like SAP Analytics Cloud, businesses will no longer need to suffer due to electrical and other technical issues since every data is accessible from any device and at any time.
Dresner opined that as of 2020, the cloud Business Intelligence adoption rate is reported to be the highest in the manufacturing sector at 58%. It is much higher than the financial industry and business services, which are at 40%.
- It Improves Decision-Making
As mentioned earlier, SAP Analytics Cloud helps employees to make the right decisions using data-driven insights. The platform also empowers employees and allows them to develop self-confidence, essential for building strong and motivated teams.
Team members can learn to use analytical data in small and big sets to generate insights independently as per their needs. These insights make way for effective planning and actionable decision-making to achieve both short and long-term goals.
- It Offers Advanced Modeling Functions
There’s good news for manufacturers; they can now gain complete control over their data and even customize it as per their business goals. It’s possible because SAP Analytics Cloud comes with powerful modeling capabilities that are fully compatible with the SAP S/4HANA ERP system.
Using these modeling features, manufacturing teams can clear all their junk data and gain more accurate analysis. What’s more, one can get a better view and understanding of all business data through the card view mode. Users can create multi-level hierarchies, set up advanced formulas, fix errors and issues on a large scale, and more.
- It Organizes Dashboards
All the relevant data is made available to the team members through organized and more customizable dashboards. These user-friendly dashboards help to display data in a more attractive and comprehensive format that makes it usable.
As per ZDNet 2019 reports, around half of the companies worldwide, that’s 45%, use and rely on some kind of cloud-based big data. To achieve that end, one needs organized dashboards like SAP Analytics Cloud, designed to make information more easy-to-read and understand and boost information consumption.
- It Improves Data Accessibility and Distributes Data Efficiently
It’s easy to integrate SAP Analytics Cloud with one’s existing applications that can centralize vital data and make it more accessible across all departments. Analytics Cloud comes with practical design solutions that can enhance data visualization and smoothen the data sharing process across the system.
With this platform, manufacturers can now manage multiple entities and business partners with ease and greater flexibility. The best part is, manufacturing companies can share any data with partners, colleagues, vendors, teams, and distributors via any device at one go!
SAP Analytics Cloud is an effective solution that helps to scale and secure your manufacturing business by transforming your workflows over the cloud. This agile and secure cloud-based solution allows manufacturers to overcome challenges like data growing unmanageable, lack of proper connections, and growing inconsistency among data sources.