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November 1, 2017

Demystifying SAP Leonardo - Building a System of Intelligence

"SAP Leonardo will unlock the full potential of the intelligent enterprise" - Bill McDermott

SAP Leonardo is a cloud-based intelligent system focusing purely on building "self-driving business" using digital business transformation. It integrates breakthrough latest technologies and services under one umbrella. It helps enterprise digitally transform SAP system as System of record to systems of intelligence. 

Beyond the IOT to Broader Bundle of Technologies  

SAP Leonardo is not a single tool, platform or system like SAP Cloud Platform, HANA or S/4HANA that enterprise needs to start the digital journey. It has innovative portfolio of technologies & design thinking as service to get started with the digital journey. The idea is that customer can take advantages of these emerging technologies at the same time bringing in the Design Thinking approach. It is imperative when working with a system of innovation or for a large transformation Design Thinking increases the success rate.  The combination together defines Leonardo.


How it is different than the other MI based products 

Combination with Design thinking approach enables a customer to quickly put together ideation, identifying the use case to solve & bringing technologies in an integrated way to deliver working prototype which business can touch & feel. 

In the age of digital, the transformation for business are no longer technology led rather they are Business innovation focused. SAP Leonardo enables customers to innovate easily without a much lower investment in technologies, data scientists & infrastructure.

Why now this 

SAP recognizes Digital Transformation within an enterprise requires a combination of next-generation technologies. It is utmost important for customers to build a system of intelligence by connecting it to a system of transactional records (ERP) to automate processes, enables connectivity and quickly adopt to game-changing applications - or develop solutions to power new business models. SAP understands and recognizes the need to have solution which are beyond SAP technologies and therefore it has

        - Invested heavily in cloud and IOT platform

Partnered with apple, google, Siemens ...etc

        - And enabling the platform to work on open source technologies 

Adopting SAP Leonardo services is a step towards embarking on the journey of creating a system of Intelligence - it is not a question of if but when 

1. It is the beginning of SAP Leonardo: Emerging technologies like MI and IOT has a traction in the Industry, but we are at an interesting position which is at beginning of an exciting journey to fully understand it's potential. 

2. Design Thinking led approach: It enables to navigate from ideation to rapid prototype, the concept of "Fail Early , learn Early" helps in identifying the right business case 

3. Go slow not big: "See, touch and feel" enables enterprises to embark on pilot to initially validate the solution and its feasibility within their business

4. Think holistically: The digital transformation for enterprises should be Business innovation focused, not technology focused. Enterprises that adopt "best in class" processes will experience enhanced metrics for cost and quality performance.


Over the past few decades SAP has empowered us to deliver quality services to the business, customers and employees using its core ERP. Consumers use intelligent assistants and expects the same conversational interaction and intelligence with their business software. SAP Leonardo provides combination of emerging technology enabling enterprises to be much closer to a more exciting digital journey, where the current system of record can be transformed into System of intelligence. Technology is advancing at a rapid pace and enterprises need to move rapidly in order to gain the competitive advantage over others and not investing in your systems is not an option anymore. 

Several organization are embarking this journey, the question for you is "are you ready"?  


May 22, 2017

Data Quality as a Service - Infosys DQneXT


Previous Blog : We discussed "Data Quality as a Service - The Challenge and The Opportunity"


Infosys Data Quality Solution - DQneXT

"DQneXT" is Infosys's comprehensive Data Quality solution that addresses many of the Data Quality requirements of an Organization. The DQ solution is based on SaaS model, multi-tenant and hosted on Infosys's SAP Cloud Platform. The architectural advantage of this solution in comparison to a traditional DQ tool are as illustrated below



Typical Data Quality Program

Infosys - DQneXT

*      Typically On premise

*      Multiple tools for profiling, enrichment & deduplication

*      Rules are created for every customer

*      Timeline for implementation of 3 domains is 4-6 months

*      Mostly target master data

*      Annual License cost is applicable

*      Cloud based multi-tenant solution

*      SaaS based solution that works on subscription model

*      One stop shop for profiling, enrichment, de-duplication and more

*      Starts with a rich library of Rules 

*      Timeline for onboarding is in days

*      Goes beyond master data to handle transaction & configuration data

*      Flexibility to pick and choose services & pay as you go


 Services offered under DQneXT

Infosys offers a combination of several services that are typically desired by most Organizations in a single packaged application. These services are typically employed at different stages of the data quality program from Data Discovery to Data Archival. The different packaged services and their relevance in the data quality life cycle are illustrated below


  • Data Profiling Service

Data Profiling is a basic service aimed at providing insights into the current quality levels of data. This leverages a rich repository of rules for each domain consisting of frequently used business rules, industry standard rules and technical rules that drive the data maintenance in SAP. These profiling services help understand the status of enterprise data quality and help establish the cleansing requirements for the data. The data can be analyzed along various dimensions like Accuracy, Consistency, Completeness, Integrity, Duplicacy, etc. The data quality is measured against defined thresholds and represented in business friendly dashboards. There is provision for report extraction for business review and corrections.

  • Data Enrichment Service

Data enrichment service provides the capabilities for ensuring the identified issues with data are fixed using automated fixing rules. They can be leveraged for bulk and routine fixes where a large number of records have similar issues. The pre-determined fixing rules and capabilities help shorten the data remediation cycle times and helps prepare data for "Fit to Use"

  • Configuration and Data Management Service

This is a special service aimed at next set of capabilities that help proactively identify and resolve issues with configuration data quality that impacts business process and transactions. They are used for early detection of bad data in transactions that could be due to configurable, obsolete or restricted data that impacts the end processes and could cause downstream impact to business.

  • De-duplication Service

The de-duplication service is an essential service that finds use in duplicate identification and survivorship. Typical used cases are

(1) Identifying duplicate records from historical data and

(2) Prevention of new duplicates at the point of creation of data

The one time identification of duplicate data helps get rid of duplicate records in system and identify the surviving records. This cleanup helps in making unique data available to business transactions for consolidated reporting and analytics. Similarly, the prevention of creation of duplicate data helps in keeping system clean going forward basis and yielding better search results improving the overall health of organization's data.


Key benefits of this solution

The DQneXT solution / service offering has been designed keeping in mind the evolving trends in the industry leveraging the SaaS based offering on cloud called DQaaS. This has significant benefits compared to the traditional approach of on premise DQ tools pre-dominant in today's market.

  1. Client need not invest in expensive infrastructure, licenses and sign up for annual maintenance services
  2. Works on subscription model with flexibility to choose required services without having to pay for unwanted modules/services
  3. Packaged services with comprehensive offerings including profiling, enrichment, proactive problem identification and de-duplication
  4. Quick Client on-boarding process with pre-set processes that can be realized in a matter of few days
  5. Pre-delivered rich repository of rules consisting of master, transactional and configuration rules
  6. New rules added to the repository on an ongoing basis become available to the Clients at regular intervals without any significant cost or effort


Conclusion

Infosys DQneXT provides muti-dimension capabilities for identification and resolution of the data quality problem that Organizations try to address through multiple industry standard licensed tools. This provides a cost effective and efficient alternative to the businesses that are adapting to the cloud based services.



Next Blog : We will discuss "FAQ's on DQneXT "


May 10, 2017

Digital Disruption & SAP S/4HANA: Journey so far and the way ahead

 

As I write, this is no more a buzz and we are standing at the dawn of the digital disruption. The impact of the digital technologies can be seen around in our personal lives too. How we communicate, engage and interact with one another. Convergence of technologies like social media, mobility, analytics, cloud computing, business networks and embedded devices are leading the way.

This is not the first time there is disruption, Right from, the Industrial economy to information economy changes in 1940-1980, in 1980 onwards we saw, satellite systems for different business functions like, order management, inventory management, manufacturing, finance started integrating and gave rise to evolution of ERP suites, after 2000 industry started sighting changes in the business models because of the rapid expansion of the internet. And when now things have become digital, there exists opportunities to design and integrate these digital assets, which were earlier not designed to work together and produce business benefits. Technological innovations further paving the way for digitalization and leading to an era of digital transformation and, is now poised to create a spectrum of the opportunities to create new business models. But unlike previous disruption, this time it is rapid and demands the response from the organizations also similar in nature, to remain in the game.

Envisaging the fact of upcoming tsunami of digital, SAP Introduced SAP S/4HANA Finance in 2014 and a completely new enterprise suite SAP S/4HANA Enterprise Management with a digital core in Nov 2015, in order to create a digitalization friendly platform. SAP's roadmap for the ECC suggests that support to ECC will cease to exist in 2025 and no significant changes expected in future ehps. Since the launch of S/4HANA, about 4200+  customers either adopted or in the process of adopting S/4HANA against the estimate of 50000+ by 2025. Out of the 4200 a good number is of the customers who are first time implementing SAP, thus the number of customers who actually embraced S/4HANA away from ECC is less. It is to be noted, many organizations were still transforming or had completed their transformation with SAP ECC and other peripheral SAP applications in recent times only.

But reasons for the initial slow adoption of SAP S/4HANA could be many - why to adopt, how to get there, availability of skill, product maturity, Business case, budget... and many more questions are there in client's mind. Research suggests that when it comes to innovation adoption, there can be four categories of the companies. Market Leaders, who actively go for the change and prefer to drive it. They look technology as enabler in the disruption. They accept failure as part of the process and move on. Fast followers react based on the success of the market leaders and the result of their experiments. But contrary to the market leaders, they do not want to fail and apply lessons learned from the market leaders to their roadmaps. Cautious adopters, as name suggests, take more measured approach spend time in studying and instead of transformational, they adopt approach of incremental innovations. Laggards procrastinate the adoption and wait for the trends to move beyond. They constitute 50% of the marketplace. Whereas fist three category constitute 5, 15 & 30% respectively. SAP S/4HANA adoption may also fit in the theory. In my experience too, clients who were not showing any interest in S4HANA last year, are now serious to discover and explore it for a business case.

Another dimension, do majority of the companies aware of, why they need SAP S/4HANA? or it is just that date of year of '2025' which is making them to go for it. Clients are exploring and also getting education about the various transition paths to S/4HANA, difference of features between ECC and S/4HANA, timelines and cost of implementation/conversion. They are looking S/4HANA as an upgrade from ECC, however current situation demands different approach. I think, if companies do the same things after adopting S4HANA, which they were doing with ECC, that is not transformation. Merely replacing ECC by S/4HANA will not add as much business value and unleash the benefits of the digital core.  The current trends suggest, with digital transformation, companies have to get into the transformation mindset and have to create new business models along with the new products and services. Companies have to align with innovation scope, explore options in design thinking workshops and come out with a roadmap for a digital journey. Here SIs, SAP with S4HANA will help companies to reinvent their business models.

 

It is widely established that, we are well in the disruption and the norm is, disrupt or will be disrupted. There is no denial that ERP is the DNA for every company and thus adoption to S/4HANA becomes crucial for every organization. Studies shows that average age of the companies have decreased. Companies have to reinvent themselves to stay in the business. What is going well now may not work in future. The definition of "end" is going to change when we talk about end to end. Companies have to look SAP S/4HANA as a platform to start their digital transformation journey and have to focus on B2B2C instead of B2C.

SAPPHIRENOW 2017, Orlando is just around the corner now, and is the opportunity for the companies to visit our booth #700 to get more insights on how Infosys can help them in their digital transformation journey using S/4HANA. Infosys has S/4HANA Adoption service offerings and tool set to help client adopt S/4HANA either by S/4HANA Conversion of their ECC systems, Consolidating ECCs using Landscape Transformation and adopting S/4HANA or whether to go for Hybrid or Greenfield implementation. Come to Infosys booth, and we can showcase, how our clients have adopted S/4HANA in different ways and how we can help you with our automated S/4HANA Assist tool to perform S/4HANA Assessment.


Continue reading " Digital Disruption & SAP S/4HANA: Journey so far and the way ahead " »

May 9, 2017

"Data Quality as a Service" - The Challenge and The Opportunity

"Data Quality as a Service" - The Challenge and The Opportunity


Overview

Enterprise data quality is no more an option. It is expected by Customers, demanded by business and enforced by regulators. Awareness on data quality and its impact on day to day operations and ultimately the business has been increasing steadily over last couple of years. Organizations have realized, good quality data is the foundation for an Organizations growth and sustenance in the long run. Poor data quality plagues the Organization in more than one ways and has direct and indirect costs associated with it. Data quality challenges impediment the growth of organizations and unreliable insights are persisted to other strategic initiatives that leads to lack of trust in enterprise data and can result in poor business decisions. Organizations have thus realized the need to manage Enterprise Information as a strategic asset and are finding ways and means to improve the value of this asset.

Though data quality tool vendors have been around in the market for a considerable duration, they have not been able to influence the adoption much. With growing economies, Organizations have had other focus and priorities like acquisitions, growth, market capitalization, expansion, etc etc. Slowly, the underlying problem with the data has grown multi-fold having escaped everyone's attention. This is seemingly apparent now as the businesses continue to grapple with "the data problem" that has reduced the operational efficiency, interfering with decision making and posing a larger threat if not controlled immediately.


The Challenge

Some of the key challenges associated with data quality include:

  • Data Quality is perceived to be one time initiative requiring significant time and money
  • Data assets lack clearly defined ownership
  • Most Organizations lack a well-defined strategy and governance for improving data quality
  • Ongoing data governance & sustenance is a key issue in master data & data quality programs
  • Data proliferation & duplication due to inadequate business rules and stewardship
  • Lack of consistent repeatable way to measure and score data quality


How big is the challenge?

Below are some snapshots of the key data problems and it's magnitude of impact on Organizations as estimated by some of the Industry's leading analysts. It clearly indicates the different nature of data quality issues and it's implications on operational and financial well-being of the Organization.



The Opportunity

As more organizations continue to focus on data quality, and as different departments within an organization continue to focus on their data elements, it presents a huge opportunity for the Vendors of the data quality tools and the service providers who help Organizations manage their data quality. Analysts estimate that only about 10% of Organizations have formal metrics for data quality, about 25% have informal metrics and rest do not measure data quality at all.

Gartner estimates that Data Quality Tools market is among the fastest growing in the enterprise software sector and continues to grow strongly year on year. It is currently growing at 13.5% and forecasts that this market's growth will accelerate to 16.7% by 2018, bringing the total revenues for Data Quality tools market to $2.24 billion.


Evolution of Organizational needs

In the context of the above opportunity, we see further evolution of Organizational needs that reduces the Total Cost of Ownership and at the same time deliver more comprehensive solutions that addresses different requirements in managing the life cycle of data quality. Some of the key requirements are

  • Look out for "Data Quality" as an end-to-end service 
  • Overcome limitations of licensed products. Ex Different tools for profiling and transformation
  • Need for continuously improving business rules to cater to the changing nature of business
  • Identification and archival of unused or redundant data on periodic basis for improved search and better performance
  • Proactively identify issues that arise due to configurations and suggest corrective course of action


"DQaaS - Data Quality as a Service"

With the advent of SaaS, the traditional approach of owning data quality applications on Organizations own computers or in own data centers is losing steam.  There is growing interest in the provisioning of data quality as a service and the vendors that provide this service. This is giving rise to a new breed of SaaS enabled services focusing on Data Quality termed "DQaaS - Data Quality as a Service".

Data quality software as a service (DQaaS) refers to data quality functions such as profiling, validation, standardization, matching, cleansing etc. delivered over web using a cloud-based or hosted model in which an external provider owns the infrastructure and provides the capabilities in a shared, multitenant environment used by its customers on a subscription basis. This provides a reasonably quick alternative to otherwise expensive and time-consuming deployments of data quality tools or the development of custom-coded solutions.


Next Blog : We will discuss "Data Quality as a Service - Infosys DQneXT"


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