{"id":4144,"date":"2016-05-24T16:31:20","date_gmt":"2016-05-24T16:31:20","guid":{"rendered":"http:\/\/www.odbms.org\/blog\/?p=4144"},"modified":"2016-06-03T08:34:51","modified_gmt":"2016-06-03T08:34:51","slug":"on-data-analytics-and-the-enterprise-interview-with-narendra-mulani","status":"publish","type":"post","link":"https:\/\/www.odbms.org\/blog\/2016\/05\/on-data-analytics-and-the-enterprise-interview-with-narendra-mulani\/","title":{"rendered":"On Data Analytics and the Enterprise. Interview with Narendra Mulani."},"content":{"rendered":"

“A hybrid technology infrastructure that combines existing analytics architecture with new big data technologies can help companies to achieve superior outcomes.”–Narendra Mulani<\/strong><\/p><\/blockquote>\n

I have interviewed Narendra Mulani<\/strong>,\u00a0Chief Analytics Officer, Accenture Analytics<\/a>.<\/em> Main topics of our interview are: Data Analytics, Big Data, the Internet of Things, and their repercussion for the enterprise.<\/p>\n

RVZ<\/p>\n

Q1. What is your role at Accenture?<\/strong><\/p>\n

Narendra Mulani<\/strong>: I\u2019m the Chief Analytics Officer at Accenture Analytics and I am responsible for building and inspiring a culture of analytics and driving Accenture\u2019s strategic agenda for growth across the business. I lead a team of analytics professionals around the globe that are dedicated to helping clients transform into insight-driven enterprises and focused on creating value through innovative solutions that combine industry and functional knowledge with analytics and technology.<\/p>\n

With the constantly increasing amount of data and new technologies becoming available, it truly is an exciting time for Accenture and our clients alike. I\u2019m thrilled to be collaborating with my team and clients and taking part, first-hand, in the power of analytics and the positive disruption it is creating for businesses around globe.<\/p>\n

Q2. What are the main drivers you see in the market for Big Data Analytics?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Companies across industries are fighting to secure or keep their lead in the marketplace.
\nTo excel in this competitive environment, they are looking to exploit one of their growing assets: Data.
\nOrganizations see big data as a catalyst for their transformation into digital enterprises and as a way to secure an insight-driven competitive advantage. In particular, big data technologies are enabling companies with greater agility as it helps them to analyze data comprehensively and take more informed actions at a swifter pace. We\u2019ve already passed the transition point with big data \u2013 instead of discussing the possibilities with big data, many are already experiencing the actual insight-driven benefits from it, including increased revenues, a larger base of loyal customers, and more efficient operations.\u00a0In fact, we see our clients looking for granular solutions that leverage big data, advanced analytics and the cloud to address industry specific problems.<\/p>\n

Q3. Analytics and Mobility: how do they correlate?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Analytics<\/a> and mobility<\/a> are two digital areas that work hand-in-hand on many levels.
\nAs an example, mobile devices and the increasingly connected world through the Internet of Things (IoT) have become two key drivers for big data analytics. As mobile devices, sensors, and the IoT are constantly creating new data sources and data types, big data analytics is being applied to transform the increasing amount of data into important and actionable insight that can create new business opportunities and outcomes. Also, this view can be reversed, where analytics feeds insight into mobile devices such as tablets to workers in offices or out in the field to enable them to make real-time decisions that could benefit their business.<\/p>\n

Q4. Data explosion: What does it create ? Risks, Value or both?<\/strong><\/p>\n

Narendra Mulani<\/strong>: The data explosion that\u2019s happening today and will continue to happen due to the Internet of Things <\/a>creates a lot of opportunity for businesses. While organizations recognize the value that the data can generate, the sheer amount of data \u2013 internal data, external data, big data, small data, etc \u2013 can be overwhelming and create an obstacle for analytics adoption, project completion, and innovation. To overcome this challenge and pursue actionable insights and outcomes, organizations shouldn\u2019t look to analyze all of the data that\u2019s available, but identify the right data needed to solve the current project or challenge at hand to create value.<\/p>\n

It\u2019s also important for companies to manage the potential risk associated with the influx of data and take the steps needed to optimize and protect it. They can do this by aligning IT and business leads to jointly develop and maintain data governance and security strategies. At a high level, the strategies would govern who uses the data and how the data is analyzed and leveraged, define the technologies that would manage and analyze the data, and ensure the data is secured with the necessary standards. Suitable governance and security strategies should be requirements for insight-driven businesses. Without them, organizations could experience adverse and counter-productive results.<\/p>\n

Q5. You introduced the concept of the “Modern Data Supply Chain”? How does it differ from the traditional Supply Chain?<\/strong><\/p>\n

Narendra Mulani<\/strong>: As companies\u2019 data ecosystems are usually very complex with many data silos, a modern data supply chain<\/a> helps them to simplify their data environment and generate the most value from their data. In brief, when data is treated as a supply chain, it can flow swiftly, easily and usefully through the entire organization\u2014 and also through its ecosystem of partners, including customers and suppliers.<\/p>\n

To establish an effective modern data supply chain, companies should create a hybrid technology environment that enables a data service platform with emerging big data technologies. As a result, businesses will be able to access, manage, move, mobilize and interact with broader and deeper data sets across the organization at a much quicker pace than previously possible and place action on the attained analytics insights that could help it to more effectively deliver to its consumers, develop new innovative solutions, and differentiate in its market.<\/p>\n

Q6. You talked about “Retooling the Enterprise”. What do you mean by this?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Some businesses today are no longer just using analytics<\/a>, they are taking the next step by transforming into insight-driven enterprises<\/a>. To achieve \u201cinsight-driven enterprise\u201d status, organizations need to retool themselves for optimization. They can pursue an insight-driven transformation by:<\/p>\n

\u00b7 Establishing a center of gravity for analytics<\/em> \u2013 a center of gravity for analytics often takes the shape of a Center of Excellence or a similar concentration of talent and resources.
\n\u00b7 Employing agile governance<\/em> \u2013 build horizontal governance structures that are focused on outcomes and speed to value, and take a \u201ctest and learn\u201d approach to rolling out new capabilities. A secure governance foundation could also improve the democratization of data throughout a business.
\n\u00b7 Creating an inter-disciplinary high performing analytics team<\/em> — field teams with diverse skills, organize talent effectively, and create innovative programs to keep the best talent engaged.
\n\u00b7 Deploying new capabilities faster<\/em> \u2013 deploy new, modern and agile technologies, as well as hybrid architectures and specifically designed toolsets, to help revolutionize how data has been traditionally managed, curated and consumed, to achieve speed to capability and desired outcomes. When appropriate, cloud technologies should be integrated into the IT mix to benefit from cloud-based usage models.
\n\u00b7 Raising the company\u2019s analytics IQ<\/em> \u2013 have a vision of what would be your \u201cintelligent enterprise\u201d and implement an Analytics Academy that provides analytics training for functional business resources in addition to the core management training programs.<\/p>\n

Q7. What are the risks from the Internet of Things? And how is it possible to handle such risks?<\/strong><\/p>\n

Narendra Mulani<\/strong>: The IoT<\/a> is prompting an even greater focus on data security and privacy. As a company\u2019s machines, employees and ecosystems of partners, providers, and customers become connected through the IoT, securing the data that is flowing across the IoT grid can be increasingly complex. Today\u2019s sophisticated cyber attackers<\/a> are also amplifying this complexity as they are constantly evolving and leveraging data technology to challenge a company\u2019s security efforts.<\/p>\n

To establish strong, effective real-time cyber defense strategy, security teams will need to employ innovative technologies to identify threat behavioral patterns — including artificial intelligence, automation, visualisation, and big data analytics \u2013 and an agile and fluid workforce to leverage the opportunities presented by technology innovations. They should also establish policies to address privacy issues that arise out of all the personal data that are being collected. Through this combination of efforts, companies will be able to strengthen its approach to cyber defense in today\u2019s highly connected IoT world and empower cyber defenders to help their companies better anticipate and respond to cyber attacks.<\/p>\n

Q8. What are the main lessons you have learned in implementing Big Data Analytic projects?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Organizations should explore the entire big data technology ecosystem, take an outcome-focused approach to addressing specific business problems, and establish precise success metrics before an analytics project even begins. The big data landscape is in a constant state of change with new data sources and emerging big data technologies appearing every day that could offer a company a new value-generating opportunity. A hybrid technology infrastructure <\/a>that combines existing analytics architecture with new big data technologies can help companies to achieve superior outcomes.
\nAn outcome-focused strategy that embraces analytics experimentation and explores the possible data and technology that can help a company meet its goals and has checkpoints for measuring performance will be very valuable, as this strategy will help the analytics team to know if they should continue on course or need to make a course correction to attain the desired outcome.<\/p>\n

Q9. Is Data Analytics only good for businesses? What about using (Big) Data for Societal issues?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Analytics is helping businesses across industries and governments as well to make more informed decisions for effective outcomes, whether it might be to improve customer experience, healthcare or public safety.
\nAs an example, we\u2019re working with a utility company in the UK to help them leverage analytics insights to anticipate equipment failures and respond in near real-time to critical situations, such as leaks or adverse weather events. We are also working with a government agency to analyze its video monitoring feeds to identify potential public safety risks.<\/p>\n

Qx Anything else you wish to add?<\/strong><\/p>\n

Narendra Mulani<\/strong>: Another area that\u2019s on the rise is Artificial Intelligence<\/a> \u2013 we define it as a collection of multiple technologies that enable machines to sense, comprehend, act and learn, either on their own or to augment human activities. The new technologies include machine learning, deep learning, natural language processing, video analytics and more. AI is disrupting how businesses operate and compete and we believe it will also fundamentally transform and improve how we work and live. When an organization is pursuing an AI project, it\u2019s our belief that it should be business-oriented, people-focused, and technology rich for it to be most effective.<\/p>\n

———<\/p>\n

As Chief Analytics Officer and Head Geek \u2013\u00a0Accenture Analytics<\/a>, Narendra Mulani<\/strong> is responsible for creating a culture of analytics and driving Accenture\u2019s strategic agenda for growth across the business. He leads a dedicated team of 17,000 Analytic professionals that serve clients around the globe, focusing on value creation through innovative solutions that combine industry and functional knowledge with analytics and technology.<\/em><\/p>\n

Narendra has held a number of leadership roles within Accenture since joining in 1997. Most recently, he was the managing director \u2013 Products North America, where he was responsible for creating value for our clients across a number of industries. Prior to that, he was managing director \u2013 Supply Chain, Accenture Management Consulting, leading a global practice responsible for defining and implementing supply chain capabilities at a diverse set of Fortune 500 clients.<\/em><\/p>\n

Narendra graduated from Bombay University in 1978 with a Bachelor of Commerce, and received an MBA in Finance in 1982 as well as a PhD in 1985 focused on Multivariate Statistics, both from the University of Massachusetts.<\/em><\/p>\n

Outside of work, Narendra is involved with various activities that support education and the arts. He lives in Connecticut with his wife Nita and two children, Ravi and Nikhil.<\/em><\/p>\n

———-<\/p>\n

Resources<\/strong><\/p>\n

–\u00a0Ducati is Analytics Driven.\u00a0Analytics takes Ducati around the world at speed and precision.<\/a><\/p>\n

– Accenture Analytics. Launching an insights-driven transformation. \u00a0Download the point of view on analytics operating models to better understand how high performing companies are organizing their capabilities.<\/a><\/p>\n

–\u00a0Accenture Cyber Intelligence Platform.\u00a0Analytics helping organizations to continuously predict, detect and combat cyber attacks.<\/a><\/p>\n

– \u00a0Data Acceleration: Architecture for the Modern Data Supply Chain, Accenture<\/a><\/p>\n

Related Posts<\/strong><\/p>\n

On Big Data and Data Science. Interview with James Kobielus<\/a>,\u00a0Source: ODBMS Industry Watch,\u00a0<\/span>\u00a02016-04-19<\/span><\/p>\n

On the Internet of Things. Interview with Colin Mahony<\/a>\u00a0Source: ODBMS Industry Watch,<\/span>\u00a02016-03-14<\/span><\/p>\n

A Grand Tour of Big Data. Interview with Alan Morrison<\/a>,\u00a0Source: ODBMS Industry Watch,\u00a0<\/span>2016-02-25<\/span><\/p>\n

On the Industrial Internet of Things. Interview with Leon Guzenda<\/a>,\u00a0Source: ODBMS Industry Watch,\u00a0<\/span>\u00a02016-01-28<\/span><\/p>\n

On Artificial Intelligence and Society. Interview with Oren Etzioni<\/a>,\u00a0Source: ODBMS Industry Watch,\u00a0<\/span>\u00a02016-01-15<\/span><\/p>\n

 <\/p>\n

Follow us on Twitter: @odbmsorg<\/a><\/strong><\/p>\n

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