Data War between SAP & Hyper Scalers to introduce AI/ML into Customers’ Enterprise Data

In Google President’s words on SAP Relationship, Ron said, "We (Google) don't want to compete with SAP on industry technologies in that way. SAP are experts at the business process layer. We think we can add value with AI, ML, and data analytics."

SAP CEO Christian Klein recently quite assertively stated that “while it’s all nice and wonderful that the big hyper-scalers like Microsoft, Google Cloud are forging tighter partnerships with SAP, those hyper-scalers have to remember that the partner controlling the strategic customer relationship (customer data) is SAP”.

So, what is in it for SAP customers in these two statements?

SAP has clear road map for an Intelligent Enterprise. SAP with its own S/4 HANA based Predictive Analytics Library (S/4 HANA PAL), provides ability for customers to build their own (and sometimes provides off-the-shelf solutions) intelligent enterprise framework.

At the same time, obviously, Google would like to have access to the SAP Customers’ transactional data and leverage its Artificial Intelligence/Machine Learning expertise to offer insights into the customer data.

Now, let’s have a closer look both the solutions offerings:

SAP’s view:

SAP’s Intelligent Enterprise is about enabling customers to effectively user their data assets to achieve their desired outcomes faster. At the core of the IE is Machine Learning. The world’s most relevant enterprise data is part of SAP’s own system on which the customers run their business.

Customers can manage the package delivered models by retraining and debriefing them directly within their applications. Furthermore, customer and partners can adapt predictive use cases, or create new ones based on their own business needs in SAP Predictive Analytics in S/4 HANA. Some examples are discussed below with some technical details:

Machine Learning: Process Out-sorted Billing Documents in the Utiliteis Industry

SAP’s ML utilizes previous decisions from the agent to release out-sorted billing documents or to correct these documents (such as reversal). Since the customers’ system usually contains a huge number of historical documents that have already been processed, the machine learning solution can use the corresponding master data, transactional data and additional calculations based on it to make a prediction: The release of the out-sorted document is recommended and can be processed automatically (label: Release Document) or the agent must process and check the document manually (label: No Release).

To enable such ML platform to work, SAP ships pre-packaged untrained model (model UTI_BI_OUTSORTED) and CDS Views & ABAP Report REML_BILLING_OUTSRTD_RELPRED. SAP suggests that the Machine learning-relevant information for each run is stored at DB level.

In the above scenario, here are the advantages that SAP has over a third party entering into its system to read and build machine learning:

• SAP owns the data in its own proprietary database

• SAP provides CDS Views (a new data modeling infrastructure where data models are defined and consumed on the database rather than on the application server)

• Predictive Analytics Library provides repository of classic and universal predictive analysis algorithms in data mining categories like Clustering, Classification, Regression, Association, Time Series, Preprocessing, Statistics, Social Network Analysis, Recommender System, and Miscellaneous.

For customers using SAP’s PAL to build ML capabilities, advantages are:

• IS-U Master Data, Transactional Data & Machine Learning Processing Information, stays in Industry Solution – Utilities (IS-U) system.

• Machine Learning takes advantages of CDS views

• ML algorithms need not have to go out of their native infrastructure which provides great advantage over time, speed and data transfer latencies.

Hyperscaler’s (Google) view:

Google to deploy its ML on SAP’s Enterprise Data.  To achieve this, Google should get copy of the enterprise transactional data as it may not interpret the SAP’s CDS views and leverage the data model.

This may result in latency while google is attempting to provided suggesting for the user, in real time scenarios.

Key take away:

Our opinion is that SAP S/4 HANA based Machine Learning implementation helps utilities to avoid data redundancies, speed and flexibility.

Enriching Emergency Response business processes with Geospatial, AMI & Preference Center

In the AMI era, Utilities have an obligation to leverage technologies and infrastructure to ensure safety of their customers. Enterprise Resource Planning (ERP) and Customer Experience/Relationship Management (CxM) software tools play a critical role in responding to the emergency situations. This is done mainly by deploying required resource to take control of the emergency situation, for example, a fire emergency in an apartment complex or downtown area. 

Despite the fact that required resources are deployed, on time to take control of the emergency situation, it is still possible that the emergency situation has spread around and caused more than thought of damage. 

uPrefer has partnered with MediaAgility to address Emergency situations faced by Utility Customers, at a time when enterprises are forced to adapt Postmodern ERP Models. “Google/ S/4 HANA Geospatial enabled AMI+UtiLitics® Solution” provides Utilities the capability to respond to the emergency scenarios quickly by leveraging the available Advanced Metering Infrastructure, SAP Certified Enterprise Preference Management (UtiLitics®). 

Use Case: Minimize damage caused by fire emergency in a densely populated apartment complex or downtown.

Situation: Apartment complex is equipped with Electric AMI & Gas infrastructure. Utility has implemented SAP Certified Customer Preference Management solution. Fire accident takes place in an apartment/group housing. Several customers with medical conditions exist. How to minimize the damage?

Key pain points :

• Difficulty to identify the nearby assets to act on
• Customer communication is not interwoven into the emergency situation management
• Customer preferences based communication not integrated into emergency situation management
• Lack of ability to alert the nearby public, to divert traffic from the emergency site
• Existing infrastructure software usage is limited to back office
• Integration of existing infrastructure software with ERP systems, require specialized skills that has impact on TCO

[Please use the link below to access the slides that explain the process]

https://youtu.be/YD3Yileyai0

In slide 6 of the video presentation, complex 1 has an emergency situation and it is possible that groups of houses 2, 3, 4, 5, 6 & 7 are closed to the emergency spot.  To contain the damage, it is good to remotely turn off groups of houses from 1 to 7.  Emergency notification should be sent to all customers in the geographic location.

uPrefer & MediaAgility Solution:  Utility company receives emergency call.  SAP based CxM System provides visual of the geographic location including apartment complex building.  CSR or the Control Center identifies the building(s) that can be remotely turned off for Electricity.  System provides the visual of the apartments that have customers with medical conditions.  System provides visual of Gas supply connection that must be turned off. The user selects the area and buildings on the map. System prompts the user for required action. Upon confirmation of the activity, systems sends communication to customers, based on their preferences like, Phone Call, SMS, E-mail, Twitter posting, Facebook posting. System (in collaboration with Municipalities, Apple, Google) flashes emergency alerts to the nearby Phone users to stay away from the emergency location or suggesting an alternative route for travel (avoiding the emergency site).

https://youtu.be/YD3Yileyai0

In the picture above (slide 9), SAP CRM linked Geospatial solution provides ability for the CSR/Control center to identify the assets visually and subsequently perform the required tasks.

In the picture above (slide 10), SAP CR&B based Customer Preference Center solution houses the customer approved communication method and communication data in SAP CRM system. UtiLitics® solution leverages technologies to perform several post emergency actions in a manner that reduces the negative impacts phenomenally.   

Gartner in its publication “Post Modern ERP Trends 2014” predicted that with “the Changing of the guard; the mega vendors will no longer dominate and within next 5 years, hybrid ERPs will be the norm”. The need is for a new solution in the already crowded market is to address the following issues:

• Provides ability to pictorially select the assets on which the action is required.
• Integrates Google Maps or S/4 HANA Geospatial Infrastructure with Customer Experience Management environment for operations effectiveness and smooth flow of the process steps.
• Integrates Customer Preference Management (UtiLitics®) solution into SAP CRM environment
• Efficient communication & alert management solution
• Integrates Google Maps or S/4 HANA Geospatial Infrastructure with SAP AMI (Advanced Metering Infrastructure)
• Built on the philosophy to serve the customer by leveraging Google Infrastructure
• Google's positive impact and penetration into Enterprise Applications.

Summary:

During emergency, utilities need ability to turn off smart meters by group selection, alert customers of emergency based on their communication preferences. The solution provides ability to identify assets visually, and perform required action(s) on individual asset or group(eg. remotely turn off nearby meters and flash messages to customers) minimizing life threats & accelerating post-emergency processes. Inform customers based their communication preferences about emergency.  Send safety alerts to nearby population. Customer safety, customer experience management, technology maturity, competing for digital leadership, digital business innovations, providing new types of value. Emerging Post Modern ERPs* with deconstructing ERP suites and “users taking control back”.

About the Authors:

MediaAgility is a Listed official partner for “Google Maps for Work”. Recipient of JAPAC Partner of the Year award for Google Cloud Platform, MediaAgility is a Premier Google Apps Partner for Enterprise and SMB. uPrefer Solutions along with its flagship SAP Certified solution - UtiLitics® develops Google/Geospatial infrastructure based solutions for Utilities, in collaboration with MediaAgility.

Customer Preference Management for Utilities using SAP CR&B

In an era, when technology is transforming the way people lead their lives, it’s increasingly becoming important for companies to use state of the art technology to communicate with the customer. Effective communication can be a competitive differentiator for most companies. In order for effective communication to occur, it’s imperative for companies to honor customer preferences with regard to the content, mode/channel, and timing of communication. However, companies are facing challenges in implementing customer preference management solutions due to perceived loss of control to customers, and disparate legacy systems. In response to this need, uPrefer Solutions has developed a rapidly deployable, low cost, and scalable solution built on an existing SAP CRM framework, making Customer Preference Management an integral part of SAP for Utilities and eliminating the need for expensive third party software. This solution enables companies to effectively communicate with the customer, thereby increasing customer satisfaction, as well as achieving better sales & marketing campaign results, and ultimately, an improved bottom-line.

Why is communication with the customer important and what is a Customer Preference Management solution?

For most companies, and for Utilities in particular, customer satisfaction is the most important performance indicator. Higher customer satisfaction results in an improved competitive position, and favorable rate case outcomes for utilities. Customer satisfaction is not only a function of the quality of the product offerings, but also dependent on effective communication.

Given the wide array of communication channels available, such as mobile, email, text, and social media among others, customers are bombarded with a wide variety of information. However, information overload without regard to the customer preferences on how they can negate the effectiveness of such information. An effective Customer Preference Management solution will take into consideration customer preferences with respect to what, when and how they would like to receive information. By employing such a solution, a company can tailor its communication strategies to deliver personal, relevant, and engaging messages. An effective Customer Preference Management solution will have the following elements:

• What to receive – content type: Alerts, promotions, new products, problem situations etc.
• When to receive – frequency and time of the day: Daily, weekly, monthly, yearly, or never; Time of the day to receive such messages
• How to receive – Mode/Channel of communication: Email, text, voice messages, snail mail, social media etc.

Companies sensitive to these preferences will likely lead the way in gaining excellent customer experience going forward.

How are companies managing customer preferences currently and what are the limitations of such strategies?

Custom data storage for each preference type, which suffers from the limitations in terms of,

• Customer data sits in disparate systems throughout the organization leading to multiple views of the customer
• Synchronization between customer preference data and the customer’s communication data has to be established manually.

A third party system to store all preferences, the limitations of which are:

• Needs on-line synchronization of master data and transaction data with 3rd party system
• Customer data is stored in a 3rd party hosted server and hence cannot be used for internal analytics purposes
• High maintenance costs due to multiple interfaces

Given the limitations associated with each of the existing solutions, there is clearly a need for a solution that provides a central repository for all the customer preferences, and yet be a part of the existing systems infrastructure, eliminating the need for third party independent systems.

How is an “UtiLitics®” solution better than the existing solutions in the market?

uPrefer Solutions has developed a rapidly deployable, low-cost, and scalable solution, “UtiLitics®”  built on existing SAP CRM framework making Customer Preference Management an integral part of SAP for Utilities and eliminating the need for direct and indirect costs like data synchronization with third party software. The solution, UtiLitics®, is certified by SAP.  The advantages of “UtiLitics®” solution are as follows:

From a customer point of view:

• Puts customer in control of their preferences
• Provides an easy to use interface that allows the customers to manager their preferences through their chosen medium.

From the utility company point of view:

• Less custom code; built on existing framework
• Provides central repository for all customer preference data, allowing for a single view of the customer
• Reduces Call Volume by providing flexible integration with transactions.
• Since data is native to CRM, it is available for other purposes like marketing, backend processes and BI integration
• Allows for better customer experience auditing and tracing
• Allows for Statutory compliance (Do Not Call etc.)

Can you provide a high level process flow of “UtiLitics®” Customer Preferences Management solution?

“UtiLitics®” Customer Preference Management solution uses the established SAP CRM framework to make Preference Management an integral part of the SAP for Utilities. High level process flow is explained in the link provided below:

http://www.uprefersolutions.com/how-it-works/

Conclusions:

“Sophisticated Utilities need sophisticated solutions”. “UtiLitics®” Customer Preference Management solution is one such. SAP Certified, low-cost and built entirely on the existing SAP CRM framework, this solution minimizes custom code, provides a single view of the customer, and integrates seamlessly into existing channels of customer communication.