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A Playbook for Managing at the Crossroads

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Innovation Beyond The Four Walls

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October, 24, 2014

Vorwerk Selects Cognizant for a Wide Range of IT Services

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The Cognizant Difference

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BIG DATA ANALYTICS

We live in a world of data abundance, but are underwhelmed by paucity of insights. The sheer complexity of storing and indexing large data stores, as well as the information models required to access and make sense of them, is burdensome to all companies, regardless of size and industry. Uncovering new insights from big data – contained in both structured (transactional) data and unstructured/semi-structured (interactional) formats -- requires prioritizing, organizing and validating on the back end and employing front-end analytical tools that are accessible to knowledge workers. It’s bigger than merely changing out technology; it also requires a delicate overhaul of key knowledge processes to ensure that signal is applied and noise is discarded.

A well-executed big data program provides the opportunity to uncover hidden markets, reveal unmet customer needs and cost savings opportunities and drive game-changing, meaningful improvements in everything from shipping efficiencies to medical treatments, to social media campaigns and related digital marketing promotions.

BEST PRACTICES

Our work with leading clients worldwide reveals the following big data analytics best practices:

  • Establish processes and organizational structures, then choose the best tools to solve high-value business problems.
  • As you experiment, continuously refine existing processes -- and create new ones -- and acquire tried and true tools to support big data. Be cost conscious, of course, but focus primarily on agility and speed of decision making, as well as ease of use by non-technical knowledge workers.
  • Don’t underestimate the importance of master data management. The need for a single version of truth is especially true for big data analytics initiatives.
  • Train your staff in the databases, technologies and ontologies required to build, manage and extend big data capture and subsequent analysis. If you lack big data analytics skills, you are not alone. Consider analytics as-a-service to provide a cost-effective, standardized way of supplementing internal talent and adding horsepower to prosper from big data analytics.

A more virtual and globalized world requires businesses to work proactively and anticipate change before it happens. Big data analytics can help businesses meet this challenge, but only if they align tools, processes and organizational structures to advance operational agility and deliver business results.

  • Our Latest Thinking

Trade Surveillance with Big Data
Real-time, high-frequency trading (HFT) is placing increasing pressure on regulatory compliance teams to keep up with and monitor the industry's widening pools of structured and unstructured data. Emerging technologies can help capital market firms use big-data analytics to collect, classify and analyze high volumes of data to formulate strategies for better surveillance, compliance and spot abuse.
Semantic 'Radar' Steers Users to Insights in the Data Lake
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
Informed Manufacturing: Reaching for New Horizons
Although still in its infancy, informed manufacturing -- making the right information available in the right form at the right time -- is advancing across industry sectors. Cognizant's recent in-depth study involving interviews with manufacturing CXOs, engineering firms, service and IT providers, academia and industry analysts worldwide, revealed that while most companies understand the significance of informed manufacturing, many are proceeding carefully -- working to balance the conflicting priorities of managing day-to-day business while focusing on innovation and breakthrough initiatives. They see external support as a critical success factor.
Developing a Comprehensive Safe-Driving Program for Teens
Teen driving is a critical concern for families and a top-of-mind issue for insurers. Today, using advanced technologies such as telematics, the SMAC (TM) Stack (social, mobile, analytics and cloud), insurers offer all-inclusive safe-driving programs that help predict and prevent teen-related accidents--in real time.
Making Analytics Actionable for Financial Institutions (Part I of III)
To maximize ROI from their analytics platforms, financial institutions must build solutions that explicitly, visibly and sustainably enable real-time translation of data into meaningful and continuous improvements in their products, services, operating models and supporting infrastructures.
Safeguarding Bank Assets with an Early Warning System
The recent global financial crisis underscored the impact of non-performing assets and caused banks' overhead to soar. An automated early warning system (EWS) can help these institutions avoid the risk of problem loans, better protect their assets and reduce the effects of delinquent payments.
Bank(ing) on Data Science
By embracing data science tools and technologies, banks can more effectively inform strategic decision-making, reducing uncertainty and eliminating analysis-paralysis.
Income Replacement and Data Analytics: Retirement Planning for the Future
While governments and financial institutions work to achieve long-term stability, the unstable economic landscape threatens to significantly reduce the working population's retirement income and assets. The Income Replacement Ratio (IRR), supported by data analytics, is becoming an important factor in structuring future retirement products and helping more plan participants achieve their retirement goals.
Turning Customer Knowledge into Business Growth
By embracing big data and predictive analytics to create multidimensional customer profiles, companies can make more informed business decisions that better anticipate customer needs, wants and desires.
The Economic Value of Data: A New Revenue Stream for Global Custodians
Global custodians' big data offers myriad opportunities for generating value from analytics solutions; we explore various paths and offer three use cases to illustrate. Data aggregation, risk management, digital experience, operational agility and cross-selling are all covered.
 

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