Analytics & IoT

By Satyakam Mohanty, Director and CEO, Ma Foi Analytics

Satyakam Mohanty, Director and CEO, Ma Foi Analytics

Ma Foi Analytics is a data centric insights advisory firm, offering outcome oriented business solutions by combining capabilities in data sciences (analytics, research) & Big Data Technology, to help organizations with faster decision making, customer retention, increased revenues and profitability.

Symbiotic Relationship between Analytics & IoT

We strongly believe that IoT and analytics would have a symbiotic relationship. With continuously increasing use of IoT devices there is huge magnitude of data that is getting generated and analytics industry breathes on data. Moreover, if we look at the analytics industry, it is moving towards automation and machine driven algorithms. Now with IoT generating reams of data, the bigger ask is how do you metabolize these data and feed into a machine learning interface which brings out insights and recommendation from mundane activities of you customers. The real differentiator would be the ability to substitute largely inefficient and piece meal human elements in the process with automated tasks and sub-processes based on triggers from IoT sensors. Thus, we strongly believe that analytics would definitely aid IoT to become more decisive and directional to their customer.

If we look around, most consumer facing brands which are developing IoT devices are focusing on making these devices more intelligent for the user. This phenomenon is revolutionary for the analytics industry as analytics would no longer be bound to organizational decision making but lead to democratization of analytics usage for individual decision making.

On the other hand, analytics usage is going to increase for both early adopters such as BFSI, e-Commerce and the emerging industries. Among the emerging industries we see tremendous enthusiasm from retail and process manufacturing whereas industries such as public sector units which we believe are going to be most benefited by analytics implementation in decision making have been comparatively slow. 
Challenges in Analytics

Among many we believe that lack of data collection capabilities and inertia to change internal IT structure for enabling data collection are the most significant challenges in developing an analytics practice. Although many industries have realized the importance of implementing analytics, yet that realization has not been pervasive and internal analytics teams have faced challenges in finding internal consumers or champions of analytics.
If we look at Indian market these hurdles are even graver and companies have not been open to partner with specialized analytics firms. Moreover, we believe that developing synergistic relationship with specialized analytics firm would help firms setup and embed analytics within existing processes faster and achieve buy-in from organizational leadership and internal stakeholders.

Future Trends

Big data has occupied a disproportionate chunk of conversations for some time now. In 2014, organizations invested millions on infrastructure, manpower and cloud based platforms in their effort to tame the Big Data monster. 

We believe that the key trends in the Big Data space in the coming year will have a huge impact not only on how organisations deal with Big Data, but more importantly on what impact this will help on the world around us and how organisations could use it to drive the outcomes they seek. Given below are the trends that will be witnessed:

Mobility will come of age: With smarter phones and wearable devices computing is going way beyond the PC. Already, most of the online platforms see more and more users accessing data from smartphones and tablets as from the PC.

The Cloud will become more meaningful: Cloud goes hand in hand with mobility. Most of the frequently used applications are available on the cloud – bulk e- mail and newsletter applications, survey apps etc. 

From things on the internet to the IoT: Think of how the internet and smart mobile devices created the new world of ‘big data’ in the last few years by allowing anytime, anywhere access and sharing of information with anyone! What if we were to tell you that this may soon be outdated? Enter the IoT, a brave new world where existing technologies – sensors, RFID chips, scanners, the internet and local networks enable machines and other inanimate objects to capture and stream consistent and uninterrupted data that is easy to read and analyze. The promise to change the way we live, work and do business. 

Artificial Intelligence and Robotics: Artificial intelligence and robotics will play a major role in 2015. Most wearable devices and sensors need to be aligned with the way humans think and act, so that complex work can be programmed and automated. 

Image Processing and analysis: Pixel analysis and image processing is being talked about in the Analytics industry already but will really take off in 2015. In the healthcare sector for instance, reading medical images and subsequently analysing them with accuracy and making recommendations is a real challenge. There is no software product in the market to analyse medical images and since we are heading towards another year with big data, this opportunity will ignite many minds to come up with ideas and solutions.
Cloud Automation and data security: Cloud automation and management is another emerging field, where a lot of thought seems to drive value. Automated task management gives IT the flexibility to define a task, set policies for implementation, design criteria for performance checks and finally track the events end-to-end.

Value will drive Big Data conversations: Big Data’s been bandied about so much and for so long that it’s time for people to stop talking and start doing. The focus of Big Data has largely been around three Vs: Volume, Velocity and Variety.

The Data Scientist’s role will be pivotal Analytics will go real time: The Data Scientist will work shoulder to shoulder with the software engineer in the battle for Big Data. The need to analyse and integrate structured and unstructured data from various sources and draw meaningful insights that can be acted upon and make the multi - skilled data scientist indispensable.

Analytics will go real time: A lot of excellent analytics unfortunately reaches decision makers too late to be useful.  Real Time analytics is much in demand, but has so far scarcely been available. Many companies have built the infrastructure to collect information and data for performing analytics, it is now time for these organizations to now use this infrastructure to not only perform analysis, but also to make insights available in real time so that appropriate actions can be taken, before it’s too late.

Analytics to alter the Marketing Industry

Marketers will move beyond “current state” reporting, which all too often passes for analytics, to discover the actual levers of change in their increasingly complex environments. Right-time marketing will become more and more common as businesses are able to combine and make sense out of consumer breadcrumbs across all channels of engagement in a timely manner.
New tools will enable not just the “data scientist”, but also the average marketer to easily create forecasts, determine optimal approach, automate all necessary consumer-facing actions, observe actual outcome, learn and repeat for improved results.

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