Top ten questions to ask to software outsourcing companies in India

Have you made up your mind to outsource some of your IT operations, functions or projects to softwar

 

Have you made up your mind to outsource some of your IT operations, functions or projects to software outsourcing companies in India to reap the economic and competitive benefits? Beware, your wrong decision can put your organization in trouble. Quantification of process to choose software outsourcing company can help you choose the best organization that fits the best to your requirements.  A set of questions follow to help you in this process.

1. How is your financial health?

Financial stability is vital before outsourcing your projects to software outsourcing companies. Financial stability would induce stability and timely delivery of your projects. It would also ensure that it can cope up with economic fluctuations in the market. Financial health should be given very high importance while quantifying candidate qualification. Organization can use financial rations like Debt-to-Equity Ratio, Current Ratio, Quick Ratio, Return on Equity (ROE) and Net Profit Margin. This is indicative list and not an exhaustive one. There are many other financial parameters that one should consider to determine the financial health of a software outsourcing company.

2. How is your physical health?

Company profile with sound physical statistics like employee count, office locations, running project counts, successful projects executed, year of experience etc. helps you to decide company capabilities and competencies.

3. What is your relevant experience to my domain?

Proven track record of service commitment and delivery is very vital but Industry knowledge is even more important.  A company can be sound technically but if it fails to understand business requirements, it lays the foundation of unsuccessful product or project.  User acceptance heavily depends on this factor. Even if a project is technically good, it may fail if user acceptance is not given due consideration. Industry and subject knowledge play crucial role for successful project.

4. Do you have any quality assurance certifications?

Certification alone cannot help to judge a company in terms of quality and timely delivery. However this provides an organization additional surety that the company follows specific processes that leads to quality and timely service delivery to customers. This also reflects company’s commitment and dedication to service quality.

5. How would you protect our confidential information?

Concepts, ideas and trade secrets are king in business. It floats the organization and misuse of this has ability to sink the organization as well. IP protection and confidential information are the key factors that were hindering revolution in software outsourcing for ages. However software outsourcing companies in India have started respecting the importance of Intellectual property ownership and confidential information. Companies have taken required actions to ensure that IP remains with outsourcing company and confidential information are protected.

6. What is your project management methodology?

The success of project execution is highly dependent on selecting the right software development life cycle and its project management methodologies. Project management methodologies controls the project scope, time and cost creeps. It also puts required checks on project quality and deliverables. Software companies in India have started using AGILE Project management methodologies like SCRUM for better and effective project managmenet. Right project management methodologies provide sustainable benefits at tactical, operation and strategic level.

7. How would you fit to my requirements?

Every organization has different business needs. It is important to ensure that the company that you choose is flexible and scalable enough to meet your needs and service offerings. It should be flexible and ready to go beyond a service call to ensure that your business runs smoothly.

8. How is your business model and contracts structured?

Conflicts are unavoidable and can emerge any time during or after the service delivery.  It can be due to any reason foreseen or unforeseen. Contracts and agreements are vital to mitigate legal and contractual risks. It is important that contracts and agreements are structured considering all software outsourcing risks, business needs and geopolitical boundaries and protects the organization from legal issues and conflicts.

9. What is your SWOT analysis?

SWOT analysis would help an organization to understand strengths, weaknesses, opportunities and threats of the software outsourcing company in question. A closer frequency match of SWOT analysis, ensures better sync of organizations in terms of company culture, values and work ethics. SWOT analysis also provides other meaningful information about how company is structured and where it is heading. This can help you in company analysis in better way.

10. What is your force majeure?

Natural calamity or any unforeseen event or circumstances can put your business on hold. It is very important to know how company manages and reacts to force majeure like earthquake or any other natural calamity to ensure business continuity. These terms can help to know how soon your business can be expected to resume during force majeure.

A wrong decision of choosing software outsourcing company in India can outweigh the benefits of outsourcing in terms of money, time and skills and right choice can boost your business to next level. Though this list is not exhaustive but indicative to help you choose right software outsourcing partner to reap the competitive and economic benefits of software outsourcing.

What are different types of Big Data as a Service (BDaaS)

The fame of Big Data lies within its wide-ranging definition of employing high volume, velocity, and

The fame of Big Data lies within its wide-ranging definition of employing high volume, velocity, and different data sets that are difficult to manage and excerpt value from. Clearly, most software development companies can identify themselves as facing Big Data challenges and chances today or in future. This, therefore is not a new issue yet it has a new quality as it has been aggravated in recent years. Cheaper storage and omnipresent data collection and availability of third party data has overtook the capabilities of traditional data warehouses and processing solutions. Businesses investigating Big Data frequently recognize that they lack the capacity to process and store it sufficiently. This shows either an inability to employ existing big data sets to the fullest or inability to expand their current data strategy with additional data.

Three strata of cloud computing as a service

Big Data as a Service is in the business of countless as-a-Service offerings. The most noteworthy ones that allow us to classify any subsequent services are threefold. Infrastructure as a Service (IaaS), e.g. virtual machines, networks, storage devices, or servers, is the most basic building block and includes everything (real or virtual) you would expect inside a data center. Above this level, exists the Platform as a Service (PaaS) which includes frequently employed software like web and database servers, or Hadoop and its ecosystem. At the next level is Software as a Service (SaaS) which are still nonspecific but more user interactive services like Email, CMS or CRM. Finally, past SaaS are usually domain or business specific applications.

Hadoop or a substitute distributed compute and storage technology at the platform level naturally builds the core of a BDaaS. Subsequently, any BDaaS solution includes the PaaS layer and may be SaaS and/or IaaS. This leaves us with four possible groupings for BDaaS:

  • PaaS only – focuses on Hadoop
  • IaaS and PaaS – focuses on Hadoop and optimizes infrastructure for performance
  • PaaS and SaaS – focuses on Hadoop and productivity & exchangeable infrastructure features
  • IaaS and PaaS and SaaS – focuses on total vertical integration for features and performance

Big Data as a Service Models

               

Big Data as a Service (BDaaS) offerings in the cloud can be categorized into one of four types:

Core BDaas

The core BDaaS implements the minimal platform, e.g. YARN and HDFS having Hadoop and a few popular services like Hive.  Amazon Web Service’s Elastic MapReduce (EMR) is the most noticeable core BDaaS and represents this model. EMR is one of myriad services in Amazon’s offering and EMR assimilates well with many of the other services just as NoSQL store DynamoDB or S3 storage. Users can combine them to build something like data pipelines to a comprehensive full company infrastructures around the EMR service. However, composability of its services being Amazon’s strength, also signifies that the core BDaaS offering is meant to stay nonspecific to interact with the other services.

Performance BDaaS

One way of vertical integration for BDaaS is in the downward direction to include an optimized infrastructure. This allows to get away with some overheads of virtualization and specifically build hardware servers and networks keeping in mind Hadoop’s performance needs.

Businesses are served, understanding and working with Hadoop that are rising, but are held back by scale and complexity. The software development company can outsource their infrastructure and platform needs and management around Hadoop to an infrastructure service provider. Business can then emphasize on putting Hadoop to work and the stack from SaaS upwards. A package pricing strategy based on storage and compute usage aims to remove common problems of choosing between performance and cost optimization, and give anticipated, fixed costs.

Feature BDaaS

The other way of vertical integration for BDaaS is in upward direction to include features past the common Hadoop ecosystem offerings. The feature driven BDaaS emphases on efficiency and abstraction to get users started with Big Data quickly. The feature BDaaS company’s services includes web and programming interfaces and database adapters pushing technologies like Hadoop into the background and their service reaches into the SaaS layer. In fact, Hadoop clusters are initiated, scaled and even stopped transparently according to the load requirement.

The feature method uses IaaS to provide computing and storage with a noteworthy difference. Being independent from a cloud provider allows a feature BDaaS to leverage computing and storage as a fully scalable and more importantly interchangeable commodity. Amusingly, the compute and storage from IaaS are pass through pay as you go and thus ideal for very variable, volatile, or exploratory workloads.

Integrated BDaaS

Finally, another possibility is a fully vertically integrated BDaaS that syndicates the performance and feature benefits of the previous two BDaaS. This is an interesting approach since it could result in the perfect BDaaS, which is productive and supports business users and experts, and provides supreme performance. Both feature and performance BDaaS are at initial stages and the integrated BDaaS could in practice turn out to be a good solution to this difficult problem.

Conclusion

As Big Data is growing as a topic, business and service models are evolving and we can see the similarities and differences between the three competing types of Big Data as a Service. The core BDaaS has been around for quite a time and is in use by many software development companies especially as part of a bigger architecture or for uneven workloads. It has settled as a model supporting the provider’s broader service architecture.

The feature BDaaS needs a proof to be competitive on a performance level, though the commoditization and service level generalization means that at the end of the day, winning of this model isn’t dependent on squeezing the most performance from comparable hardware, but on a dollar to dollar basis. The performance BDaaS, will face business demands from companies that diminishingly are willing to take on the complex challenges of building their own data architecture and linked SaaS layer, and progressively want to focus on their value adding domain specific processes.

 

Trends in software outsourcing this year, 2016

We have seen software outsourcing companies welcoming increased standardization and cloud computing

We have seen software outsourcing companies welcoming increased standardization and cloud computing options of all flavors, use their influence to renegotiate or rebid their deals, and settle into a best-of-breed approach to offshore outsourcing.

 Let’s look at some trends in outsourcing industry in this year:

Security becomes the epicenter

Security is on the mind from the boardroom to the break room, and it will impact outsourcing strategy in 2016. Certainly, security risk is poised to increase as telematics and the IoT becomes more prevalent in consumer and commercial products. Growing numbers of threat actors will use more and more creative ways to exploit weaknesses, often with devastating effect. Regulators will exact gradually large fines for poor security. Service providers have often been the weakest link in a company’s security and will need to find improved ways to address that concern.

The threat profile changes every day and with every additional protection comes a new weakness, not to mention it is becoming harder and harder to tie products together to deliver a robust security solution. This year, we expect to see the upsurge of the Chief Security Officer and more companies opting for specialized security vendors with Security-as-a-Service capabilities that can protect data no matter where it exists.

Offshore captives strike back

Companies will influence the experience they have gained in process maturity as a consequence of working with outsourced offshore teams and set up their own shops, predicts the objective of this tactic will be cost cutting by taking away the provider’s margin, as well as increase flexibility by removing contractual constraints. Rather than insourcing as a knee-jerk reaction to a bad outsourcing relationship and repeating previous mistakes, clients will benefit from lessons learnt and be smarter about what and how they exile.

Production workloads – hit the cloud

There’s no denial that Amazon’s first mover advantage with the public cloud. And IT shops who reached for the cloud first did so with trivial systems. But in this year, we’ll see more production workloads move to the cloud—and not just AWS. No CIO (Chief Information Officer) wants to tie up with just one cloud provider. IT pros recognize that the future of their data centers will symbolize many platforms, so we’ll start to see more CIOs experiment with other key public cloud options, such as Microsoft Azure and Google Cloud Platform.

The potential to move outsourcing from the ‘lift and shift’ of trivial processes to something more substantial is entirely doable in the cloud. The as-a-service outsourcing model makes it likely to combine infrastructure, software, and business process to create a platform that is much more segmental, scalable and intellectual. This platform can handle higher-level processes, creating results that increase revenues, improve profit margins, enhance customer service, and move the business ahead instead of running in place.

VMOs go conventional

Multi-sourcing has amplified the vendor management workload. As clients look for ways to address the challenges of managing ever more complex multi-vendor service delivery models, the VMO will establish itself as a way to provide a high-level, organization-wide view while at the same time managing day-to-day operational details and multiple touch points between different providers in the service delivery chain.

Integration challenges the flow

Customers adopting a great number of evolving digital technologies will face an ever-larger integration challenge. Many of the most powerful cloud technologies will require integration struggles comparable to those required to install ERP systems. As most software outsourcing companies in India do not have employees who are able to manage multiple emerging technology platforms, they’ll have to outsource service integration, change management and incident management. So we expect increasing partnerships among providers.

The service providers universe develops

Customers will buy from a growing list of technology providers. Customers will continue to turn to ITO, BPO, KPO, software outsourcing companies in India and cloud service providers who have radiated a digital trail for assisting in becoming digital businesses. They will source services from an ever-expanding list of evolving and digital technology providers. We’ll see more product-driven managed services as more product-oriented vendors, such as Cisco and others, move ahead than just selling their products to also delivering services around their products. We are already seeing this on a small scale, but expect it to rise this year as very large clients are growing their managed services capabilities.

Automation will reinvent relationships

Having shattered the opportunities to move work to lower-cost people, IT Outsourcing companies and BPO companies put their emphasis now on moving it to machines. Buyers with agreements designed to purchase people will need to settle their contracts to this new world. Both customers and providers will have to reconsider their deals as they integrate more RPA into IT service delivery.

Both parties will have to redefine roles and skills necessities for human jobs, as well as manage the touch points between automation functions and jobs performed by humans. This will present a substantial challenge for outsourcing relationships as agreements will need to be flexible to house these highly dynamic environments.

Agile sourcing emerges

With technology itself seeming to advance gradually, outsourcing decision making will have to speed up. Software outsourcing companies India who decide on a digital strategy will execute quickly in this year to avoid seeing a technology shift or an opponent jumping ahead. We see growing numbers of clients deploying substantial negotiating teams working on an agile basis to close smart deals quickly.

Emerging Technologies and Opportunities for Big Data Applications

Introduction Software development companies are trying to be up to date with the emerging trends for

Introduction

Software development companies are trying to be up to date with the emerging trends for Big Data. Big data has got a well-recognized place by The Government as well. Government has recognized big data by categorizing it as one of the ‘Eight Great Technologies’ which will drive the world to future growth. The (COMMUNITY, 2014) reports on the increase in data being produced and the importance of new types of computing command in order to reap the economic value of the data.

Big Data

According to (COMMUNITY, 2014), the following is a working definition of Big Data:
“Big Data refers to huge volumes of data with high level of complexity as well as the analytical methods applied to them. This requires more cutting-edge techniques and technologies in order to develop meaningful information and understandings in tangible time”.

Analytics is considered to be the inherent part of new techniques and technologies for Big Data. The scope of analytics covers three roles:

a) Descriptive analytics - to understand what is happening in the world, using visualization techniques, some modeling and regression.

b) Predictive analytics - to predict what will happen, using forecasting.

c) Prescriptive analytics - to work out what we want, using simulation, optimization, scenario testing and Multi-Criteria Decision Analysis.

Trends in Big Data Analytics

Big data technologies and practices are moving quickly. Here’s what one should know, according to (Mitchell, 2013), to stay ahead of the game :

a) Big data analytics in the cloud

This allows users to access extremely scalable computing and storage resources through the Internet. It allows companies to get server capacity as needed and expand it rapidly to the enormous scale required to process big datasets and execute complicated mathematical models. Cloud computing reduces the price of data storage because the resources are shared among many users, who pay only for the capacity they actually utilize. Companies can access this capability much more quickly, without the expense and time needed to set up their personal systems, and they do not have to purchase enough capacity to accommodate highest usage.

b) Hadoop: The new enterprise data operating system

Hadoop is by far the most popular implementation of MapReduce. MapReduce is a completely open source platform which handles Big Data. As it is flexible, it works with multiple data sources. It either aggregates multiple sources of data in order to do large scale processing, or reads data from a database in order to run processor-intensive machine learning jobs. It has several diverse applications, but one of the top usages is for large volumes of constantly changing data. Changing data may be web-based or social media data, location-based data from weather or traffic sensors, or machine-to-machine transactional data.

c) Big data lakes

Traditional database theory dictates that you design the data set before entering any data. A data lake, also known as an enterprise data lake or enterprise data hub, turns that model on its head. It offers tools for people to analyze the data, along with a high-level definition of what data exists in the lake.

d) More predictive analytics

Predictive analytics is the branch of data mining concerned with the prediction of future prospects and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other unit to predict future behavior.

With big data, analysts have not only more data to work with, but also the processing power to handle great numbers of records with many attributes.

e) In-memory analytics

It works by increasing the speed, reliability and performance when querying data. Business Intelligence deployments are typically disk-based, that is the application queries data stored on physical disks. In contrast, with in-memory analytics, the queries and data exist in the server's random access memory (RAM).

The use of in-memory databases to speed up analytic processing is increasingly popular and highly valuable in the right setting. Many web application development companies are making use of In-memory analytics to attain more reliability and greater performance.

f) More, better NoSQL

Alternatives to traditional SQL-based relational databases, termed NoSQL (short for “Not Only SQL”) databases, are rapidly gaining importance as tools for use in specific kinds of analytic applications.

 According to (Wikipedia), the working definition of NoSQL is as follows:
“A NoSQL, formerly referred to as "non SQL" or "non-relational", database provides a mechanism for storage as well as retrieval of data which is modeled in means other than the tabular relations used in relational databases.”

Conclusion

While the subject of Big Data is broad and encompasses many trends and new technology developments, Software development companies in India are keeping pace with the global market. It becomes essential for organizations to cope with and also handle Big Data in a cost-effective way. The various technologies emerging for Big data applications are Hadoop, Column-oriented databases, MapReduce, Schema-less databases, or NoSQL databases to name a few.

Bibliography

COMMUNITY, E. T. (2014). EMERGING TECHNOLOGIES: BIG DATA. HM GOVERNMENT.
Mitchell, R. L. (2013, Oct 23). 8 Big trends in big data analytics. Retrieved Apr 25, 2016, from 8 Big trends in big data analytics:
http://www.computerworld.com/article/2690856/big-data/8-big-trends-in-big-data-analytics.html
Rouse, M. (2012, June). Cloud ERP. Retrieved 04 20, 2016, from
http://searchcloudapplications.techtarget.com/definition/cloud-ERP
Wikipedia. (n.d.). Retrieved from https://en.wikipedia.org/wiki/NoSQL

 

Difference between CRM and ERP

1. Introduction Software outsourcing companies in India have witnessed that business are adopti

Software outsourcing companies in India have witnessed that business are adopting CRM and ERP systems these days to accelerate business growth. CRM and ERP are two important technology acronyms that businesses need to know about. Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) are similar in many ways, as they are both used to enhance the profitability of a business.

(solutions, 2015) says, these systems are similar in some areas, and can be completely integrated with other. However, as their central functionalities are completely different, it’s best for a business to first look at them as separate entities i.e. stand-alone systems. When viewed independently, it’s easier to see how ERP and CRM each play a role in improving efficiency and increasing sales.

What is CRM?

CRM is an abbreviation for customer relationship management. It is a phrase used to describe all facets of interaction that a company does with its customers. The interaction may be either sales related or service related.

CRM at its simplest is a system with processes for managing a company’s interactions with existing as well as potential customers.

CRM is developed to include all sectors of the customer experience so as to keep the customer happy and in turn making them loyal and more valuable to the business. It is the process of identifying potential prospects, nurturing them and guiding them through the sales process to improve the business. CRM systems like Microsoft Dynamics CRM and Salesforce provide a standardized technique for collecting and sharing customer data and classifying customer interactions.

Since all of the data is standardized, it is easily shared across the business. Various activities that CRM performs are:  used by executives to create sales projections, by sales reps to maintain communication with clients, by shipping clerks to verify addresses, and by the billing department to create invoices. This lets the executives, managers, and developers to share data in software development companies.

What is ERP?

ERP is an abbreviation for enterprise resource planning. ERP software is used to manage the business. It integrates all aspects of an operation for product, including planning, development and manufacturing processes, human resources, finance and sales and marketing.

Like CRM, ERP allows for the rapid sharing of standardized information throughout various departments. Executives, managers, and other employees all enter information into the ERP system, creating a real-time, enterprise-wide snapshot.

The prominent feature of ERP is the shared database that provides an array of functions which is used by almost all of the departments of the organization. Implementation of this software enables all the departments of the organization to access up to date information. In addition to this, the entity is also able to analyze the performance, profitability and liquidity at any point of time.

The most important benefit of this software is that as it is integrated software the redundancy of data is minimized. The software also provides standardized procedures, processes and reporting as well that are common in the industries.

Key differences between CRM and ERP

According to (S, 2015), following are the major differences between CRM and ERP:

    1. CRM is defined as software that lets the organization to trace every transaction between the clients and a customer. Whereas, ERP refers to a software program that helps the company to manage its business processes going on across the company.
    2. ERP consolidates the information provided by different functional groups of the organization through systems like CRM, Supply Chain Management (SCM), and Human Resource Management (HRM) etc.ERP was developed earlier than CRM.

    3. The CRM is mainly utilized in conducting back office activities, whereas ERP is used to accomplish back office activities.
    4. CRM is oriented towards the management of relationship with customer of the enterprise while ERP is majorly concerned with planning the resources of the organization to ensure its best possible use.

    5. CRM focuses on increasing sales, but ERP gives emphasis on reducing costs.         

Consolidated comparison chart of CRM and ERP

Basis for comparison CRM ERP
Definition It is Computer software that ensures companies to record each and every transaction and interaction with the existing and prospective customers is CRM. It is Integrated pre-packaged computer software that lets the organization to manage and control the on-going processes in the organization.
Subset/Superset Subset Superset
Focus Increasing Sale Reducing Cost
Developed in 1990 1960-1970
Orientation Customers Enterprise
Utilization Front office activities Back office activities

Conclusion

Customer Relationship Management helps the organization to maintain a long term relationship with its customers. Software development companies in India are also leveraging this benefit. In addition to this, it is also useful to know about the preferences of the clients and develop trust. CRM enables the organization to know the preferences of the clients. On the other hand ERP combines various functional units of the organization together so that they can freely share the information. It lets the various functional units to communicate with each other on a real time basis through a centralized computerized system. Apart from the above differences there is commonality among the two softwares and that is, they both aim to enhance the profitability of the company.

 Bibliography

S, S. (2015, September 11). Differences Between CRM and ERP. Retrieved 04 21, 2016, from Differences Between CRM and ERP: http://keydifferences.com/difference-between-crm-and-erp.html

solutions, S. S. (2015, June 11). CRM vs ERP. Retrieved 04 21, 2016, from CRM vs ERP: What’s the difference?: http://www.sysco-software.com/crm-vs-erp/