Month: September 2021

Usage and Features of SAP S/4HANA that can make Retail Management Easier

Posted on by stridely

SAP S/4HANA is an advance enterprise resource planning solution that comes with in-built intelligent technologies such as machine learning, AI, and complete analytics system. This application suite allows retail businesses to improve their business models, while offering them insights to crucial operation data. It also empowers them with real-time, contextual information for better and faster decision-making.

Besides the above, the solution also provides users the agility and flexibility needed for ensuring best in the class customer experiences. The intuitive and simple interface of SAP empowers the retailers to create faster and smarter retail solutions by leveraging forecast foundation and data set provided by the system. In other words, it simplifies their business processes and IT landscape for unlocking business innovation.

Success Case: SAP S/4 HANA Implementation On Cloud: Machinery Manufacturing Company

Let’s see how it is highly useful and feature-rich for retail management purpose for the enterprises.

SAP S/4HANA – Usability

SAP S/4HANA is deployed in the cloud system of the companies of all industries and sizes. However, there are several factors that are considered to determine the factors that requires this system and its usability for their retail business.

The system builds actually guards the applications for encouraging clean data entry. With this system in place there is no need for creating inflexible tools for accommodating the day to day requirements of the user and business that keep changing from time to time.

Also Read: Digital Transformation and SAP S/4 HANA – All that you need in this swiftly-changing and competitive world

The particular needs of the users is to be considered here when it comes to automating the system using SAP S/4HANA. Also, it is important to find the right balance between budgets and product backlog of the retail business. With system in place the users can get continuous feedback which not enhances the development process but also allows the project team to deploy their resources on various functionalities that can prove out to be more valuable for the end users.

When it comes to improving the usability it’s important to find the right tools for the job considering the following aspects –

  • Form factor where the system is to be implemented – Determine whether the user will access the functionality from a handheld scanner, desktop, or tablet.
  • What kind of decision is to be made by the user – Do the user needs the application for interaction purpose, or merely exporting a report to Excel serve as a better option for reaching that decision?
  • Whether extra money and time is required for customizing UI5 development for adding all relevant features – or is it important to use ABAP RESTful for creating a simple and quick Fiori application.

Also Read: Why is it Essential for You to Migrate to SAP S/4HANA Right Now?

Keeping the above listed consideration in mind allows businesses to ensure a better user experience while helping them to avoid mistakes that may otherwise arise if a wrong tool is built for retail management.

End users’ choices and preferences are to be focused here as SAP S/4HANA for retail management is primarily implemented for them. And they will be the ones interacting with this system on a regular basis.

Accepting and embracing the technology has become need of the hour as it makes the lives of individuals easier. Optimal usage of the application is important for retailers to improve the overall data quality as it is the main element empowering their analytical tools.

SAP S/4HANA – Features

By introducing S/4HANA, SAP has ensures a much more modern and personalized user experience in comparison to SAP GUI. However, during the implementation process it is challenging to customize that experience for user base of a specific retailer as it involves a number of activities such as custom programs testing, system configuration, interface building, data conversion and more.

Also Read: The Right Time to Migrate to SAP S/4 HANA

Read on explore the application’s major features to learn how it benefits in retail management –

Enables Multi-Level Contract – A proper procurement process is important for the retailers to meet the industry standards. It provides them the ability of maintaining stock and supply orders with suppliers in advance. Making precise decisions is difficult at early stages.

SAP S/4HANA’s multi-level contract feature allows retailers to consider high level commitments and provide additional details to the supplier later on. In the meantime, it gives retailers the flexibility of reacting to the market changes. The feature eliminates the possibilities of overstocking and allows retailers to maintain a healthy relationship with their suppliers.

Flexible commitment contract is though an old concept but today it has a number of new features. It allows the users to sign a ‘source contract’ with their vendors (mentioning generic article only for the meanwhile), and the exact variants can be specified later.

Fulfils Purchase-to-Order or Third Party Order efficiently – SAP S/4HANA allows users to handle decoupling of purchase order and sales order articles in case a customer reduces the order quantity or cancels a sales order.

SAP S/4HANA eases the work of retailers that comes with a purchase order cancellation. With this application in place they need not to deal with exhaustive system changes as the entire process is automated. Moreover, retailers need not to create any new buying orders as the system automatically checks what all items are available in the stock and whether they are sufficient for fulfilling new sales orders.

Also Read: Confused about whom to choose as SAP HANA Managed Services Cloud provider?

However, it is to be noted that the system works efficiently when the article/merchandise of the required variety are aligned. The alignment of purchase-to-order or third-party order items with the freely available, pre-existing purchase order articles enable optimal consumption of purchase order items.

Handling pre-pack purchase orders – Pre-pack handling requires flexibility as the retailers may not be aware of the exact structure or composition of a pre-pack article at the early stages of the process but still want a purchase contract to secure their order for generic articles which may become the part of pre-pack or structured article later on. The pre-pack components mentioned in the purchase call-off contract can be taken as the reference.

Data change automation – The application’s smart features allows retailers to differentiate between different use cases. It allows the customers to easily access the item collection. Plus,   retailers can add new collections and styles and remove collections or styles from the list. Moreover, they can modify the priority. All these processes are automated by the application.

Value Added Services features – Earlier users could add a VAS to their merchandise or product but it involved the risk of transpiration if a particular plant or center involved in distribution couldn’t carry out the service or fulfill the request. The advance SAP S/4HANA can now easily combat this issue as it comes with a ‘plant capability check’ feature. An order document for stock transport and sales order inclusive of VAS isn’t allowed if the order can’t be provided in a particular location.

Re-determining seasons for various items – The advanced Season Master Data feature of SAP S/4HANA gives users an indication whenever a new season re-determination is required. After the Season Completeness application is processed for an order item, an indicator for season completeness indicator is assigned to it for avoiding seasons’ redetermination for articles with a pre-determined season.

Handling workflow and class-based events – Users can handle events with exceptions such as the ones related to orders un-assignment. The system raises a class-based event when deviation in the orders.  They can be managed easily within the standard workflow framework where the configuration of ‘triggering event’ takes place for performing the particular tasks.

Prioritization of dynamic supply – It offers the ability of supplying assignment and manages the supply according to the different supply varieties and time intervals. Such as, warehouse stock and on-hand can be considered as a short notice demand whereas the demand which is to be shifted to the later stages can be kept for future supply. The SAP Fiori application’s ‘Configure Supply Sort Rule’ can be considered for rescue as it allows users to prioritize specify time and different types of supply.

Evaluation of Documents by Supply Demand Overview – Earlier, the Supply Demand Overview displayed data and info of ARun related items. The users couldn’t a detailed picture of the objects through it.  SAP S/4HANA is now capable of visualizing the entire supply and demand status with the help of data sources including Open Supply, Temporary Assignments, Open Demand, Preview Assignments, and Normal Assignments.

Demand selection as per supply – At times it is important to identify the various elements of demand assigned to a supply. For example – inbound for outbound process that allows the users to stay updated of the incoming deliveries related to supply assignment but you want details of demand elements that are assigned for the process. The enhanced version for ITA has comes with two new tabs allowing STO and SO selection by the supply assigned for the purpose. The selection criteria of the new tabs can be used for selecting the current assignments.

The Final Takeaway

User experience is one of the major aspects that the retailers need to consider when implementing SAP S/4HANA.  Building the right support and functionality for the project can be done easily by the implementation team by engaging the users in the process. The settings can be made relevant for various SAP S/4HANA Retail business apps by getting them customized for General Logistics, Distribution and Sales, Cross-Application Components, and Materials Management.

Start Leveraging SAP S4HANA for Retail Management

Stridely Solutions can deploy SAP S4HANA for enterprise digitization or help you migrate from your legacy systems to it – fully or partially. For retail businesses, we utilize the best industry practices and optimize the IT spending positively. Whether you want to get started right now or need consultation services first, Stridely SAP experts are available to mentor and work with you.

 

SAP BW/4HANA – Data Tiering Optimization (DTO)

Posted on by stridely

Businesses evolve over time. They expand, scale up, procure new systems, go through mergers and acquisitions, ditch old processes, adopt new ones, build products, enter new regions, and migrate. Every change like this impacts the process and data environment, making it difficult to manage the data volumes in both transaction and data-warehouse systems.

Also, they accumulate a huge chunk of business data to fulfill their daily operations and during the real-time reporting or analysis processes.

Considering it all, your organization’s data is bound to grow exponentially. Data Growth will eventually increase the storage costs and have the huge impact on the system performance.

SAP BW/4HANA lets its users do data tiering optimization (DTO) capability to prevent problems. Read ahead and learn what it is.

Multi-Temperature Data Management

Businesses have all type of data. Some data is used rarely while other is required frequently. If you could dynamically move the rarely-accessed data to a low-cost and low-speed data storage for archiving, it will reduce data storage cost heavily and positively for your organization, isn’t it?

Multi-temperature data management makes it possible.

It classifies data in different storage areas according to the utility and usage frequency. Here’s how this classification is done:

 

Data Tiering in SAP BW/4HANA

In SAP BW/4HANA, if you want to perform Multi-Temperature Data Management, data tiering, i.e. create data tiers, has to be the first step of yours. Criteria for creating data tiers can be (but not limited to):

  • Data Type
  • Usability and Criticality for Operations
  • Frequency of Accessing the Data
  • Data Security Needs

Data Tiering Optimization in SAP BW/4HANA enables customers to set all the storage options and configure tiers using a central UI (user interface)

It is an important process for business data, as it helps organization in streamlining their operations, administering the data, and updating the storage. It not only optimizes the memory footprint of data but reduces the total cost of ownership (TCO) effectively.

Source – SAP

Standard Tier (hot): SAP HANA stores hot data in its in-Memory.

Extension Tier (warm): Extension node is used for data storage purpose.

External Tier (cold): External Storage space, such as SAP IQ, Hadoop or SAP Vora, is used for data storage instead of filling up the SAP HANA database.

Standard and Extension tiers form a logical unit and are available for SAP users in your organization almost immediately. However, external tier is located out of your SAP deployment and required you to deploy security arrangements to make it non-vulnerable.

Data Tiering Optimization (DTO) for Advanced Data-Store Object

DTO helps customers in data classification in SAP BW/4HANA. You can determine the cost and performance needs of your business data and shift it to warm, hot, or cold data storage accordingly.

There are few prerequisites to enable DTO through Advanced DSO.

  • The Data Store object (advanced) must have at least one key field.
  • To store data in the external layer, partitions must be defined.
  • SAP BW/4HANA 1.0 Support Package 4 or above.

Implementation Procedure

  • From “General Tab” of ADSO, under “Data Tiering Property” – select the data tiering type standard layer (hot), extension layer (warm) or the external layer (cold).
  • Based on the selected data tiering option, choose the method to transfer the data to specified storage layer i.e. using partition or by object type. To store data in the external layer, partitions must be defined first.
  • Object Level Temperature Maintenance – It refers to entire data set from ADSO.
  • Partition Level Temperature Maintenance – Partition must be created based on time characteristics (0CALDAY, 0CALMONTH etc.) to break down the ADSO data volume into smaller data sets.
  • Partitions can be created from the settings Tab of ADSO by specifying lower and upper limit for specific time characteristic. I.E. If we select 0CALYEAR, we can specify lower and upper limit year wise 2010 to 2011, 2011 to 2012 and so on.
  • Using RSOADSODTOS T-Code, we can further define temperature for individual portioned year (or time characteristic) based on our requirement.
  • DTO job shifts the data to its allotted storage space at pre-defined time intervals. Further, you may automate these jobs using the process chain type – Adjust Data Tiering.

Conclusion

Multi-Temperature Data Management is an efficient way to classify organization data and save storage cost without putting your business data at risk. With SAP BW/4HANA, the process becomes effortless once data tiers are configured by SAP experts. Need our help in it? We are immediately available. Contact SAP BW/4HANA specialists at Stridely Solutions today.

 

CRM Ecosystem: A Quick Overview to What you are Missing Out

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CRM or Customer Relationship Management; this is one term that businesses of all sorts are aware of and leaves no turn to attain maximum excellence. Streamlined and impressive CRM is what lays the foundation of a successful business as this operational area allows a business to value its customers and deliver its services as the customers expected or desired.

CRM is not a one-man’s job. It involves multiple sections and can only help you out when there is a synchronization between all these parts.

Watch here: Superior Decision Making with Dy CRM

In this post, we’re going to talk about the key role players of a CRM ecosystem, its importance, and ways to empower it. So, let’s get started.

CRM Ecosystem- The Success-driven Factor

A CRM ecosystem is not a term used collectively for vendors or stakeholders. It refers to a group of CRM constituencies that are co-related and form the entire Enterprise CRM ecosystem of an organization.

For beginners, CRM constituencies are the components responsible for the relationship building between a business and customers. Some of the key CRM constituencies, responsible for building a company’s CRM ecosystem, are:

  • Internal management team
  • Customers
  • Stakeholders
  • Third-party service providers

Let’s have a detailed understanding of these components:

  • The Internal Management Team 

The very first component of any CRM ecosystem is the internal management team or the business itself (in the case of a start-up or small business).

The entire CRM ecosystem stands on this constituent as it’s where the inception of CRM strategies and business-customer relations begins. There are a couple of models like the IDIC model, CRM Value Chain Model, and QCI model that one can follow to build a management team.

  • Customers 

The whole point of having a CRM strategy or put efforts to empower it is to attract or retain more & more customers. Customers are what drive success for a business and they are one of the most vital parts of a CRM ecosystem.

As the buying behavior of the customer changes, the other constituency of the CRM ecosystem has to take needed actions to increase customer satisfaction.

  • Stakeholders of a Business 

The third CRM constituent refers to the stakeholder or group of stakeholders, investing in the business. Because of their investment only, a business runs. Hiring the management team and buying crucial CRM systems is possible only if there are stakeholders in a business.

  • Third-party Service Providers 

It refers to any service provider who is helping a business to ensure improper implementation of CRM strategies. CRM is no longer a job done manually. There are various tools & technologies required for the automation of reporting and collecting accurate data. To reduce the complexities of CRM and helping businesses to contrive impressive and result-driven CRM strategies, we have CRM systems. This constituency refers to the vendors selling the license of CRM software & applications to the business.

Depending upon the type of deployment preferred by the business, these vendors can take care of CRM system maintenance, deployment, and upgrade as well.

CRM Systems- Empowering Customer-Business Relations in Best Possible Manner 

Gone are the days when running a business was all about profit and loss. Today, it’s all about customer experience and satisfaction. CRM system is designed to take care of this aspect only.

CRM system is an application, driven by AI, helping businesses to manage, collect, and analyze customer data. By deriving results from the customer data, the CRM system helps the sales department to make data-driven decisions, allows businesses to have an in-depth understanding of customer behavior, and let the marketing team do targeted marketing.

This is just the tip of the iceberg. There are tons of various other tasks that a reliable CRM system can perform.

Here are some of the key benefits of using a CRM system:

  • Time-saving 

The CRM of today’s era is empowered by automation. Starting from entering customer data to creating reports, the CRM system brings the power of automation in everything and allows end-users to save a huge deal of time.

  • Improved productivity 

When time is saved, it’s obvious that the team is going to experience great productivity. More actions can be taken in less time and businesses are going to achieve their goals speedily.

  • Timely and trustworthy reporting 

To make the right decision, businesses must have access to accurately analyzed data and informative reports. CRM system allows you to go deeper into available data & metrics and derive results from them.

  • Simplified collaboration  

With features like instant messaging, self-service tools, and email sync, CRM systems are going to simply & speed up collaboration at every level. Whether you’re collaborating with customers or with co-workers, CRM is going to perform this job with full perfection.

Types of CRM System 

No two business needs are the same. Keeping this fact in the mind, CRM systems are also offered in multiple types. The three key types are:

  • Desktop-based CRM system
  • Server-based CRM system
  • Cloud-based CRM system
  • Desktop-based CRM system 

It runs on a single device and is entirely managed by the business. The vendor only provider the CRM system license. End-user has to bear the start-up, installation, security, and maintenance-related expenses. For effective operation, one has to have a skilled in-house IT team

  • Server-based CRM system

Mostly used by huge enterprises and business houses, this kind of CRM system has a dedicated central database, managed on a server. Mostly, such CRM systems are self-hosted and are installed on each team members’ device.

Just like the desktop-based CRM system, it also comes with hefty initial set-up costs and forced end-user to take care of set-up, installation, and maintenance-related hassles.

  • Cloud-based CRM system 

This one is the most famous type of CRM system as there are no set-up and installation worries for end-user. The vendor takes care of all these and many other operational aspects by charging a monthly fee.

It’s is accessible from everywhere as this CRM system is deployed online.

From the cost and affordability aspect, we must admit that this is one of the most pocket-friendly options available as end-users are not forced to take care of the set-up, installation, and maintenance cost. There is no need to own a dedicated in-house IT team to look after it.

Speaking of mobility, it’s hard to bear a cloud-based CRM system as one can access it on any of the data-driven devices.

What Should Include in An Ideal CRM System?

A CRM system is of no use without the below-mentioned features:

  • Contact Management- This feature is here to save and collect all the key & updated features of the customers and allows a business to build an informative customer database. All kinds of contact details and service conversations are handled here.
  • Lead Management– Using this feature, the CRM system can keep tabs on the pipeline activities, figure out the useful leads, and manage the leads carefully.
  • Sales Forecasting– This feature is useful for a salesperson to have a better hold over the future picture of the company’s sales and figure out what actions are needed to improve the sales figures.
  • Instant Messaging- Connect with the employees and the customers in a blink of an eye using this feature. Real-time instant messaging functionality allows businesses to gather customer feedback and suggestions instantly.
  • Email Tracking and Sync with Outlook- Instant email syncing allows a CRM system to connect with customers and business people instantly and exchange data without any delays.
  • File and Sharing Content- Share crucial information over a single click using the file-sharing integration. It has a huge impact on the team’s productivity.
  • Dashboard-based Analytics- Things become easier than ever then when crucial information is presented intuitively. The dashboard feature of the CRM system makes this happen as everything essential is represented in a useful manner.

Other than these basic features, few advanced CRM systems can go beyond usual and offers marketing automation. Call center automation, and help-desk automation.

Things to Keep In Mind While Buying a CRM System  

The CRM system indeed holds the power to build the bond between customers and businesses. However, this is going to happen only if it’s the best of the breed. Here are some of the qualities to look after in an ideal CRM system:

  • It should be easy-to-use and supports customization
  • Preferably based on cloud
  • There should be a mobile app and multiple integrations offers.
  • The vendor should offer multiple subscription plans to meet a different kinds of business needs.

Future of CRM 

Customers are going to play a crucial role in a business’s success today and tomorrow. This isn’t going to change. One other thing that isn’t going to change is the ability of CRM systems to leverage CRM operations and empower a CRM ecosystem.

As we march ahead towards the future, CRM systems are going to be more & more crucial. It is at the heart of every growth-seeking business. The current market predictions show that the CRM market is going to touch the mark of  $80 billion by 2025.

Wrapping Up 

Before you dream of touching success highs, don’t forget to strengthen the business-customer relations. CRM system is going to help you big time. The advanced AI and a bunch of crucial features have it an indispensable part of business growth.

Its adoption is going to empower the CRM at multiple levels and let the businesses have a constant focus on the growth. Go ahead and make CRM a part of your business ecosystem.

Hire experts from Stridely to guide and help you towards CRM adoption.

Data Science – Everything That One Should Know About This Cutting-edge Technology

Posted on by stridely

If there is one thing that can change the face of an organization in no time is the quality data and its effective utilization. You may not know this but by simply using the internet around 2.5 quintillion bytes of data every day. Imagine the picture when data generated from all kinds of resources is taken into account.   

While there is no shortage of data in today’s world, its effective utilization is the only thing that will make data existence worth full.  

Data science is what makes it possible. From the day data has been considered as a vital growth-driving factor, data science has come to the forefront. So, what’s data science? What types of data science exists? What’s its lifecycle? 

These are some of the key questions that we’ll answer in this blog. So, stay tuned for more. 

Data Science – Knowing the Basics and Definitions 

Speaking of data science definition, it’s a multidisciplinary approach used for extracting useful insights from the set of given data. It involves multiple tasks like data discovery, preparation, data analysis, predictions, and data reporting to get the desired results. These tasks are also known as the lifecycle of data science.  

Have a look at these steps of data science from close: 

  • Data discovery is the process of finding out resources to extract data for the organization. This phase involves framing the business problem and formulating the initial hypotheses (IH) to test. 
  • Data preparation is the process of cleaning the data set, choosing the accurate data, data aggregation, and manipulation of data. Its key aim is to prepare the data for further processing. Performing ETLT (extract, transform, load, and transform) is a key step of data preparation.  
  • Data analysis is the second stage which involved the usage/development of algorithms, analytics skills, an AI model to extract information from the prepared data set. It’s widely done using the help of software and technologies. 
  • Data model planning is the next phase of data science. It involves determining the methods and techniques used for establishing correlation or relations between different variables to frame the foundation of the algorithms used in the next phase. This phase involves the use of visualization tools and statistical formulas for performing quality Exploratory Data Analytics (EDA).  
  • Data model building is that phase of data science wherein a data scientist has to prepare the datasets for testing and training purposes. At this stage, you must confirm if your tools are sufficient for model execution or there is a need for more powerful tools. Let’s say, you might need a more robust environment for speedy and accurate processing of the data in parallel. For this, clustering, association, and classification like model-building techniques are used. 
  • Data prediction means combining the data analysis results to conclude something. It involves the usage of data visualization tools to represent the results. 
  • Data science – overall – involves handling all sorts of data such as raw data, unstructured data, and structured data. With time, the face of data science has changed. When it came into being, it was the job assigned to mathematicians or statisticians. Presently, there are data scientists and data analysts handling the job of making data work for the organization in a positive way. Technologies like machine learning, deep learning, and artificial intelligence or AI are used for data analysis these days. 
    On a general basis, data scientists are professionals having an ideal combination of computer and pure science skills to handle data in an expected manner. For an organization, a data scientist can handle the below-mentioned tasks.  
  • Applying given and suitable mathematics, statistics, and scientific methods to extract results from a given dataset.  
  • Using the offered or available tools and techniques, evaluating and preparing the data.  
  • Extracting useful insights from the given data.  
  • Writing applications for automating data processing and calculations.   
  • Telling and illustrating ways to convey the meaning of data processing results.  
  • Describing ways in which results can be used for addressing the business problems.  

Key Data Science Tools to Use  

As quoted above, data science is a job that can achieve accuracy and excellence only by using certain kinds of tools and technologies. Without their presence, it’s not possible to handle a huge database. From data discovery to data analysis, tools are here to speed up the process and bring excellence.  

  • Python 

Python is another very famous programming language (high-level) used for general purposes. It makes code readability effortless. There are several Python libraries, designed for supporting various data science tasks. For example, use Numpy when you want to handle large dimensional arrays. Matplotlib is good for data visualization, and Pandas can be utilized for data manipulation & analysis, and so on. 

  • R 

R is one of the most commonly used data science tools. It’s an open-source programming language used for statistical computing and graphics generation. As it offers assorted libraries and tools for data cleaning, preparation, and visualization, it’s the first choice for many data scientists.  

  • Apache Spark and Apache Hadoop 

These two are the most loved data processing platforms making things easier than ever for data scientists.  

  • Purpose-build data visualization tools 

Data visualization is a key stage of the data science lifecycle and there is no dearth of custom tools for this job. Tableau, Microsoft PowerBI, D3.js, and RAW Graphs are some of the key ones.  

  • Model building tools 

Tools like SAS Enterprise Miner, WEKA, SPCS Modeler, and MATLAB are used widely in the data model building stage.  

Data Science Use Cases In Practical World  

  • Data science has become an indispensable part of today’s digital world. From developing the apps to generating useful platforms, data science is leveraging things at every front.  
  • Using machine learning-powered credit risk models and hybrid cloud computing, a bank has created a mobile app to support the on-the-spot decisions for loan applicants.   
  • Stridely, as a leading robotic process automation solution provider, has used a high-end cognitive business process mining solution to trim down the incident handling times.  

The Final Word 

Data Science and its scope for various types of businesses can be considered to be boundless. The more skilled professionals and more complex problems your business will have, its implementations will be more helpful and precise.  

Hire experts at  Stridely Solutions for your next Data Science project and see how potent a technology can be.