Walking the distance

Infrastructure management began life as a manually provided support service, with direct access to the equipment, hardware and software. It was critical in the early days of enterprise technology when the entire setup would be delicate to say the least, and any disruptions meant hard work to get the systems up and going.

With development in technology, came remote access to the various components of a technology infrastructure, so much so that almost all issues could be taken care of, with minimum downtime or outage, from a distance.

More recently, this remote management has given away to remote diagnosis, much like medical diagnosis to prevent any issues from coming up. Every piece of software and hardware needed a defined health level, so technical personnel could monitor it according to the base requirements and then if any issues are foreseen, the concerned monitoring engineers are alerted and problems can be prevented in time. 

This proactive monitoring can prevent much larger issues from developing and causing major disruptions.

The natural progression of this path is now proactive monitoring, self-diagnosis as well as auto healing.  The systems have been successfully programmed to do a self diagnosis at specified intervals against specified parameters of health, and then run healing activities. This will help reduce workloads on human resources, while cutting down costs. The basic premise for this auto-healing is that almost all the issues diagnosed in systems are repetitive in nature, so developing tools to take care of these problems can save a lot of resources and cost. Diagnosis, prognosis and treatment- all can be done faster and more cost effectively by the machine itself.

Today we have developed sophisticated tools that self-diagnosis issues and proactively run commands to detect early stages of infrastructure issues, as well as set them right. In fact the market is moving not just towards proactive monitoring, but also towards workload automation, making it a clear differentiator. Self healing tools are fast catching up with the market requirements, and we are reaching a point where almost no human intervention will be required. The speed of recovery recorded for infrastructure bugs is faster than ever before, especially for repetitive faults.

Infrastructure management is no more manpower centric. The path ahead is about integrating this self healing with other devices- mobile devices, security centres and all other applications that will define an efficient auto-healing integrated infrastructure management system.

 

2015 – What will it look like

 

The last month of 2014, saw world leaders gather in Lima, Peru, in what was supposed to be a fight for the environment. Under the United Nations banner, high powered government delegates from 192 countries tried to reach an agreement on how to tackle the crisis of climate change. This meeting was the precursor to the mother of all meetings, to be held in Paris in 2015 – where world leaders, Presidents and Prime Ministers, will gather for the great big climate summit. The summit will be held to address the contentious issue on how the world needs to contain rising temperatures and help prevent catastrophic climate change.

The Lima conference embroiled in all kinds of climate politics, got linked to development rights, ended with what is now known as the Lima Call to Action.

Low carbon growth

An immediate fall out of the Lima meeting and the upcoming Paris climate summit is likely to find its way into the first trend of 2015 – a move towards a low carbon growth.

The need by governments, businesses and individuals to kick the carbon habit will find favoured currency. As developing countries grapple to meet their energy demands, there is every possibility that renewable could get a bigger share of the energy pie giving way to a low cost of production for renewable energy.

The likely high of 2015 will therefore be the move to low carbon emissions.

Water will matter

The Global Risks 2014 report published by the World Economic Forum, identifies water as one of the top 3 risks for governments and business. The IPCC in its latest report says that large parts of the global population will “experience water scarcity and be affected by major river floods”

How governments, businesses and local civic bodies manage water will determine the future of several countries and industries. Since 2010, there has been a growing awareness on environmental risks, such as climate change, extreme weather events and water scarcity. The Russian drought of 2010 was the first wake up call. This year California rudely fired up US government to change the way they approach water. The cost of water is likely to increase, tariffs will be higher and there will be stricter regulations on water management – from waste water usage, to recycling and rain water harvesting.

Globally there will be trend in recognising and valuing our wetlands, forests and their role in acting as sponges for water and there will be renewed thinking of the economics of water and ecosystem services.

From governments, to countries, to industries, to locals, to individuals there will be a need to get more judicious about water.

Food – the where and how

Where does it come from and how it is being grown will be asked by ordinary citizens on food and agricultural produce. Given the growing awareness on the impacts of mass produced factory farmed food on health and environment, more questions and pressure is being exerted by citizens on their governments and food companies for labelling and for responsible food production. All actors in the food chain, from cultivators, to producers, to regulators and to consumers will start making more responsible and sustainable choices.

The move will be towards locally grown and produced food.

Gender and Sexuality – the good and the bad

If Apple’s Tim Cook became a hero in 2014 for “coming out”, Microsoft CEO Satya Nadella got it all wrong. By dismissing the gender gap and blaming karma for the difference in salaries between men and women Nadella fell a couple of notches. He quickly had to retract what he said and apologise profusely. Clearly, gender remains a largely unresolved issue but not for long.

At the workplace, both these will trend in 2015 – diversity and inclusivity. Business will have targets for hiring more women specially at senior positions on a more equal footing, but also targets for a more inclusive and diverse workforce where discrimination on gender, sexuality have no role.

If these trends emerge on 2015, there is much to cheer in the New Year.

 

Supporting the connected customer

Deriving Value from Deeper Customer Insights

Excellent customer support has traditionally been the key to market success. Maintaining customer satisfaction levels would be the goal of any enterprise, specially a support organisation. But this is becoming an increasingly difficult task in a constantly connected world. While automated and connected systems and processes generate and accumulate mammoth amounts of customer data at every interaction point, not many tech support teams realise the value they are sitting on.

The tech support organisation of any enterprise is the biggest repository for customer data, and needs to learn how to store both structured and unstructured data to use it to their best advantage. In most cases, all that is required is awareness that this data bank can be a fertile ground for reaping intelligent insights. That can actually be the biggest market differentiator.

It is time that enterprises realise the value that this data can provide, with the help of the right analytics and Big data solutions. In the enterprise world today, it is this value that can be the keystone of superlative customer experience. An intelligent Big data strategy can play the most significant role in generating meaningful customer insights from these huge amounts of data. It has the capability to offer scale out, cost effective analytics framework, that adds the ability to ensure business strategies have strong data backup.

The biggest point of contention for the tech support teams and the primary reason why they do not recognise the business value for this data, because it is completely unstructured and comes from very disparate sources and the backend systems don’t have the intelligence needed to analyse the new data.

The Big data strategy needs to be based on the premise that its utility is for providing better customer service, so essentially CEM (Customer Experience management) needs to be the core layer of this strategy. The fact that this is a business strategy, with revenue implications, will ensure it is put to good use. However, there needs to also be an awareness that an analytics strategy is not merely about facts, figures and statistics. It has to do with intangibles that nevertheless add value to an engagement – excellence in agent performance and understanding customer behaviour, which build up to data collation. In order to be able to chart out an effective strategy for extracting meaningful insights not only from customer interaction content but also legacy data which is often concealed in silos, analytical tools are the best support. Since data flow is dynamic, and a constant, an analytical framework that uses a loosely coupled Big Data strategy is needed. What is needed is a clear technology layer that derives, sifts and structures data from myriad sources, and presents the right data for an efficient customer experience across all touchpoints.

Only an action driven, well supported Big Data strategy can ensure that this technology sits on a comfortable framework of customer support and will be able to offer enterprises maximum value from this data. For this, the support of a technology and strategy integrator, an intelligent partner to success is imperative.

 

Being a Service Provider in a Connected World

 

Being a Service Provider in this era of Connected World, entails delivering effective Customer Support. Effective customer support leads to Superlative Customer Experience. But this would require a 360° understanding of each customer which is easier said than done.

With an Analytics led Support Services, a support would be able to proactively provide this customer understanding

Customer Understanding -> High Attrition Risk -> Opportunity for Xsell/Upsell – > Repeat Caller, Repeat problem, High Value customer, Existing Customer Life time value -> Big Ticket Customer -> Customer Expectations -> Weekend/seasonal preferences -> Ethnicity/Demographics relativity to Customer behavior -> Customer lifecycle/interactions on various channels =Proactive monitoring/active to adaptive response based on VoC = Customer Loyalty

Thus the bottom-line implications of data mining and analytics is significant for any product/services enterprise. But the cost and complexity of setting up a data mining and analytics practice is a deal breaker for such enterprises.

Any support services provider with capability around the Social, Mobility, Analytics and Cloud service enablers can support and enable such enterprises by setting up their information management / Analytics, all at a fraction of regular time and costs of traditional solutions in the market. Thus, the desired understanding of the customer becomes a reality, so that such enterprises can start targeting the right customers for retention, sales & growth creating an impact on the bottom line.

 

Analytics led Customer Insights in a Connected World – your path to Big Profits from Big Data

 

We live in the era of Big Data and connectivity. In our ever more connected homes, humans are being taken out of the equation in a trend called home automation. Smart meters in homes can send data to utilities in order to dynamically regulate peak consumption periods, and thermostats like the Google owned(GOOGLE) Nest can ‘learn’ and adjust energy usage based on patterns. Systems, devices and physical objects are talking to one another too, adding on to the data exhaust.

For this very reason, leaders everywhere are wondering how to harness the power of all this information to improve the effectiveness and efficiency of their enterprises and institutions. All of these leaders want to know how the world’s best forward thinkers are using this Big Data to understand their environment, anticipate what it means and drive action. Analytics led Customer Insights on Big data is one area that leading Consumer and Enterprise technology products/services organization are actively getting involved with, to actually anticipate outcomes that can provide significant improvement on economic benefits.

A connected customer world offers challenges to understand customer behaviour and at the same time provide opportunities to build upon the necessary customer intelligence in a time bound adaptive manner around the following dimensions:

• Customer Identity
• Customer Intent
• Customer Intelligence

Big Data in this context is the Voice of your Customer, and with SMART Analytics provides enterprises with the ability to capture, interpret and act in real time based on signals from the market in the context of your operational data, which then provides such enterprises with the necessary Customer Insights that help them make decisions. This in turn, provides such enterprises with the competitive advantage to be a differentiator in the market.

 

Voice of the Customer(VoC), our path to Active Insight

In our quest to providing an effective tech support environment to provide a superlative customer experience, it is vital to understand the opinions that our actual and potential customers express in new channels that are much more spontaneous and less structured than the traditional surveys. The reach, the immediacy and the “emotional” aspect (Yeah, it’s all about emotional intelligence, right?) of these channels make them an impressive source of raw materials for obtaining valuable insights that can then be correlated with the traditional data collected at the tech support centre.

For this very reason, businesses are expanding their VoC initiatives towards that new territory, with active analytics on unsolicited and unstructured comments that is derived out of contact centre interactions (voice, email and chat), Social Media conversations, Blogs and News, Comments from forums and third party sites. Gartner defines customer experience (CX) as the customer’s perceptions and related feelings caused by the one-off and cumulative effect of interactions with a supplier’s employees, channels, systems or products¹. Customer experience is increasingly the single most important factor determining competitive advantage and differentiation for many organizations². According to Gartner, while 95% of such companies surveyed collect customer feedback, only 5% close the loop by letting participants know what was done based on their feedback³.

By incorporating analytics around VoC program to provide active insights, businesses can not only improve their customer experience but their bottom line as well. A sound analytics framework around tech support (capable to handle big data & analytics) can ensure businesses benefit from the massive and quick treatment of unstructured information provided by text mining and sentiment analysis technologies. The end goal is to extract the meaning from all the customer interactions correlating to their products/services/markets.

With VoC, our core focus should be on aggregating such data collected on three main dimensions:

• Customer – eg: Detect support request patterns, identify the stage of “customer journey”, detect churn and other potential risks, identify influencers, promoters and detractors, engage customers and proactively manage conversation
• Product/Service – eg: Generate insights around problem/customer, solution/product or service dimensions. Generate ideas for new offerings, identify existing issues and missing features in their product/service offerings, assess customer satisfaction and compare against competition
• Business – eg: Aggregate public opinion and media coverage around predefined variables that have an impact on business reputation (one eg: CSS Corp Analytics during one such exercise for one of our clients, identified negative sentiments around product usability correlating to customer attrition around the same timeline). This help business to act upon such leading indicators and rebuild its brand with its existing customers and general public.

A trusted tech support partner can play a big role in bringing about this awareness and then, using analytics to provide active insights on the goldmine of data you are sitting on. Such a tech support partner will help businesses build a defensible advantage in delivering superlative customer experience. These encounters lead your business to top line growth, profitability and improved customer loyalty.

¹ Lessons From 10 Consumer Brands Cited for Outstanding’ Customer Experience in U.S., Gartner, 2014

² Alcatel-Lucent customer experience survey, 2012

³ Customer Experience Management: Raising Customer Satisfaction, Loyalty and Advocacy – Gartner

Make Big Data a BIG part of your business plan

The data derived from a normal customer interaction can vary in significance across various levels. It can be hugely insightful, or just about data as is. The tragedy is, tech support teams almost always fail to see its significance in the scheme of things. The data is collated and stored, sometimes even organised and formatted, but still not used for insights. With effective technologies, tools and processes available, where is the disconnect? The shortfall has to be in the awareness of the people. They, more often than not, do not realise it would be a colossal waste not to derive market insights from it.

Most enterprises as a whole do not realise the impact this goldmine of data can have on their market positioning, strategies and even growth plans. The right data that can help derive the smartest insights is priceless. But that can happen only when the awareness of its criticality and utility in context of the business plans, is spread company wide.

Using customer insights derived from the available Big data also needs thought leadership championing. The business plans that are formed at leadership level, need the strategies to also come from the top. So it is the leadership team that needs to ensure the awareness of how significant Big data is for their business goals, becomes a company-wide goal. It is also their duty to ensure that a roadmap is created for how this resource can be used to help the company get where it should be. Every single person in the enterprise needs to be aware of the roadmap, and the role Big data can play in it. Big Data Analytics thus, needs to be incorporated into the organisational processes, and the approach needs to be top down. The flow of information for making it a part of every strategy and decision making process needs to come down from the leadership teams.

Thereafter, the second level of disconnect lies in the failure to make the data available across the teams that can actually use it as a business tool. Sitting in silos at the customer end of the process, it really serves no purpose. That dormant state can be remedied, but only after widespread awareness of its importance is created across the enterprise. The information needs to be then withdrawn from silos where it resides, and given the treatment of any other decision making tool. It needs to be led by a well defined enterprise strategy.

To get maximum benefits, enterprises have to understand the need to develop tools and frameworks that will help get data out of these silos, on a connected platform, making it available for insightful decision taking across the enterprise. Awareness of its utility needs to be the first step in this process. A trusted tech support partner can play a big role in bringing about this awareness and then, using it to leverage the goldmine of data you are sitting on.