In the diagram above, we present a roadmap to increase software process agility, starting from traditional waterfall development to build automation, test automation, continuous integration and delivery. Moving across the levels involves not only adapting processes and automating them, but also changing organizational culture and structure as needed to fully embrace this approach.
Starting from the left in the diagram, implementing Source Code Control and Build Automation are the first steps in managing software development processes. Virtually every software development organization larger than a handful of developers has implemented them.
When moving towards a more Agile process, the goals are to shorten the software development cycle and increase the frequency of software releases. Implementing Test Automation becomes an attractive value proposition as the develop/test cycle can be repeated more often. As this process of acceleration evolves in an organization, implementing Continuous Integration will allow the developers to write and test software functionality as a continuous process.
The next step is to implement Release Automation, which enables software to be automatically packaged, deployed and tested in a staging infrastructure that simulates the production environment.
Continuous Delivery, or the continuous and automated delivery of software to the end user, is the last stage in that evolution process. Typically it will include offering the software in the cloud (so that software delivery does not require updates on the customer premises or client equipment).
Software development organizations that are moving towards an increased level of Software Process Agility will see significant changes and benefits independent of where the organization is on the path, even before reaching the desired destination.
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At Daitan, we work with organizations at different stages of agility. In more conservative and regulated markets (e.g. core telecom), companies operate in a fully structured waterfall model where software goes through discrete and serial phases of development, unit testing, integration and system testing. Companies producing software that is deployed in the Cloud and offered as a service are the ones most aggressively pursuing agility in software development.
The majority is somewhere in the middle of the diagram, trying to move towards more agile software engineering processes. Most of our customers have implemented significant test automation and continuous integration capabilities and are starting to move towards extending this towards release automation and continuous delivery to end users.
To learn more about increasing your software development process agility, download our paper: Software Continuous Integration and Delivery - Increasing Development Agility and Leveraging Outsourcing
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Telecom and Software Providers Should Seize Opportunities Big Data Brings to their Contact Center Solutions
In the past few years, there has been a marked increase in the production and collection of business data. This includes a substantial portion of unstructured data from social networks, web applications and similar sources. The increasing use of mobile and sensor devices to collect information will only accelerate this trend.
The Contact Center is becoming central to the management of the customer experience and will be a source of more revenue opportunities by the use of Big Data.
When relational database management systems (RDBMS) were designed decades ago, the data we cared about was all structured. Our data models were relatively simple and our systems had limited capacity to store and process information. Today, all of this has changed.
New Big Data technologies have mostly been applied by social networks, online retailers and other Internet services to analyze operations and monitor consumer behavior. Few telecom or software solution providers understand how they can be applied to solve real-world problems in the contact center domain.
Big Data can provide a full understanding of the customers – what makes them tick, why they buy, how they prefer to shop, why they switch, what they are likely to buy next, and what factors lead them to recommend a company to others.
What is Big Data?
Big Data is a term describing the situation where the volume, velocity and variety of data (commonly referred to as the “3 Vs of Big Data”) exceeds an organization’s storage or compute capacity for accurate and timely decision making using traditional analytical systems and methods.
In traditional analytics, a data model is defined, the proper schema is set up in the database, and then the data is collected, stored and once there is a complete data set, it can be queried and the answers provided.
What if there is so much data that the system cannot handle its storage or processing? What if the data is unstructured and cannot be stored in well-defined tables? What if you would like to get answers to queries as data is still being collected? What if you need answers to new queries that were not predicted in the original data model? What if the system is so complex that you cannot fully model it?
With Big Data, storage technologies can accumulate very large amounts of data and computer processing power to test a very large number of correlations, in real-time, not just the correlations predicted in your data model after collecting a complete data set. And they can support multiple sources of data, not just the structured data sitting in well-behaved database tables.
What can Big Data do for me?
With Big Data, it is possible to deduce context, draw insight, identify patterns, and predict behavior, including:
The result of the analysis can help direct customers to the right information more effectively (hopefully even before the customer calls) or help service agents save time, ask less questions, and solve problems; resulting in a better customer experience.
For more details on Big Data technologies, including an overview of the Big Data Software Stack, please download the Daitan white paper "Big Data Technology and its Impact on Contact Centers”.
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In the past few years, we have seen a revolution on how IT systems are built and deployed. Enterprise and consumer software systems were completely re-designed to abstract its dependency on the hardware infrastructure, run in the cloud, and be accessed through mobile devices over the Internet.
The benefits are too clear to ignore and the Telecom industry is going in the same direction, with software-centric deployments using Network Functions Virtualization (NFV) on high-volume, standard hardware platforms.
In the past, most communications network functions (e.g. VoIP switches, Session Border Controllers, firewalls, media servers, deep packet inspection, etc.) were implemented as appliances, with tight integration between proprietary hardware and software from a single vendor. Scaling services involved deploying additional hardware. Implementing redundancy required duplicating infrastructures.
Recent advances in IT technology, including faster general-purpose processors capable of processing demanding real-time tasks (such as media transcoding, for example), and advances in software (e.g. virtualization technology) makes it possible to quickly deploy (minutes, not months) software components that can be made available to users to support increasing demand or to offer new services.
NFV is an architecture that breaks the various network functions into modules so that they can be virtualized. Those network functions run as independent software components without requiring awareness of the underlying physical infrastructure and without proprietary dependencies on the other network functions.
In order to validate the benefits of NFV, we have built a fully functional multi-point conferencing system and deployed it in the cloud.
Direct Cost and Maintenance Efficiencies
Improved Operational Efficiency
Minimization of Innovation Cycle
The implications are significant not only for the Mobile and Telecom Operators, but also for Over-the-Top (OTT) Communication Providers, who will feel the competitive pressure to offer integrated services and can benefit from the unbundling of integrated systems previously accessible only to large operators.
The architecture and the results we observed attest the benefits of NFV and are detailed in the white paper: "Attesting to the Benefits of NFV - Building integrated cloud-based communication services".
From Transactions to Relationships
The coupling between the phone system, dedicated hardware infrastructure, and the software solution has made the contact center a very conservative environment for decades. New entrants were kept out of the market by larger contact centers because the service and integration components of the solution were too complex and expensive for smaller companies to tackle.
But current trends that are leveling the playing field. New players are gaining ground with customer service solutions that operate in the cloud, using exclusively VoIP, with services that don’t require on premise hardware or infrastructure.
But it’s really all about the customer.
With Social Media and Mobile Connectivity becoming central to how consumers interact with brands, companies providing service through contact centers must consider customer relationships in the context of the overall customer experience to remain competitive.
Looking at the market and how the software systems supporting contact centers are evolving, we can identify the following technology trends:
For a more detailed discussion on the trends above and how both traditional and new vendors of contact center solutions can cope with it, please download the white paper, Moving from Contact Center to Customer Engagement: Using The Cloud, Big Data and WebRTC to Get There
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