newsletter | Wake up 10: What are CEOs going to ask of Big Data in the coming years?

Introduction

Taking advantage of the opportunities presented by Big Data is among the objectives of directors of Technology, Marketing, Sales and even some CEOs. Some analysts estimate the  impact of Big Data between +25-50% of additional growth  in companies and between 15-20% in the GDP of countries, depending on their ability to take advantage of the potential of Big Data.

Analysts measure the opportunity, but  not the specific paths  that companies must follow to achieve the promised benefits. The number of information sources, innovative technologies, possible business objectives and existing legal risks make finding these paths a complex task and the investments and efforts being made may fall on deaf ears.

Cognodata Vision

Cognodata has developed over the last 12 years  advanced and pragmatic methodologies to improve business and marketing productivity by combining business consulting and analytics.  During these years we have seen how more and more sources of information and process capacity have been incorporated to anticipate the needs of customers and carry out the appropriate action at the appropriate time and through the appropriate channel. But the reality is that in recent years the volume and richness of data has grown exponentially, presenting a  new paradigm .

On the other hand, the variety of  structured and unstructured data sources  and their online and intelligent processing capacity have multiplied the traces of customer behavior and the  possibilities  of interaction.

The opportunities are endless and this in turn is the  biggest risk faced by many managers  leading big data initiatives. CEOs are going to ask for tangible results in the current year, and without them Big Data risks becoming  another  bubble like the CRM bubble  in 2001.

At the time, investing in customer relationship management made perfect business sense, but software investments were made without changing business processes, and the lack of results stigmatized the CRM concept. A decade later and after many efforts to transform entities and their commercial and customer service processes, no one doubts the validity of CRM. It was an unstoppable trend, but at the time it was not exploited properly. Big Data can follow the same path if the same mistakes are made.

Proven methodology

Cognodata ‘s  vision on Big Data  is parallel to the one we developed on CRM 10 years ago, at the beginning of its second cycle. It is necessary to define a strategy that encompasses initiatives with specific business impacts and develop each of them from the data and knowledge of the client to the adaptation of processes, tools and training of people to achieve the promised economic impact.

Data:  There are three big news about data that make a method essential to identify the right questions, relevant business initiatives and analyze what data can help answer:

  • Unstructured data   such as conversations with the contact center, the texts of customer complaints, the geographical positions of mobile phones or cars, images, etc. can now be processed for business purposes
  • The data no longer comes only from the activity of the companies, but  customers, non-customers and collaborators  autonomously generate relevant information on the web and in non-traditional media
  • As we have seen in a previous graph the  volume  grows exponentially

Intelligence : The appearance of unstructured data and new unconventional sources implies that  new  data/text/web mining  techniques must be incorporated to extract the intelligence  that allows optimizing commercial action, multichannel campaigns, potential estimates, decision units , networks of influence, etc. Once again, each smart metric must exist because there are one or more business initiatives that exploit it.

Tools and processes : The Big Data era demands more of the tools and processes of financial institutions. Service experiences are increasingly distributed across a greater number of channels and customers are becoming less tolerant of disjointed silos. Application architectures must flexibly adapt to initiatives that optimize new aspects of service or business efficiency.

People : To exploit the opportunities offered by Big Data, it is necessary to act on people. Not taking into account the necessary changes in people’s attitudes and behaviors is perhaps the most frequent reason for failure. You need to apply change management techniques, advanced training, coaching, and user understanding of how data-driven intelligence can improve your productivity and customer satisfaction.

The winning strategy consists of launching initiatives with specific objectives and short-term results that value the new opportunities generated by Big Data. Each area must prioritize the initiatives with the greatest impact and ease of implementation to improve some areas of its activity. It is necessary to define a corporate strategy that  organizes the initiatives and their dependencies in a  clear roadmap until the entity is completely transformed.

An average financial institution could take advantage of between 150 and 300 relevant initiatives related to Big Data. Some examples of them:

Commercial :  Analyze  the comments entered by commercial managers after their interactions with customers to identify sales opportunities and moments in which to act on those opportunities. Put in place the  tools  that warn the manager about the opportunities identified, the reasons, give guidelines on contact strategy and  train  the network in the necessary and detailed management protocols up to specific dialogues.

Marketing : Incorporate the knowledge of ticket-by-ticket card spending to identify vital events and customer preferences. Transform campaign activity to be able to design and test hundreds of experiments to increase effectiveness 3-5 times faster.

Operations : Use the information from telephone conversations, complaints on the web, comments from managers, etc. to identify the main satisfaction drivers and their impact on customer value.

HR : Collect data from evaluations, satisfaction surveys, profiles, data on social networks, and contrast them with their financial situation in the entity, to define retention policies, profiles for new hires, analyze issues related to rotation, etc.

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