Knowledge Management amp Big Data deloitte com

Knowledge Management Amp Big Data Deloitte Com-Free PDF

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Knowledge Management Big Data,Foreword 02,Message from Confederation of Indian Industry 03. Digital Transformation through Data and KM 04,Digital Manufacturing and Supply Networks 07. Customer Knowledge to Serve them Better 13, Learning and Skilling Data Empowering the People 18. About Confederation of Indian Industry 22,Acknowledgements 23. Contacts 23,References 24, Knowledge Management Big Data.
The paradigm shift towards the digital transformation among businesses is the need of the hour Firms. are making continuous efforts to digitize their operations and investing huge amounts of money to. achieve the same resulting in increased revenue cost reduction improved customer satisfaction and. enhanced differentiation and mitigation strategies for the risk of digital disruption . The transformation is rapidly broadening the range of technologies to be used in the workplace Among. the many Knowledge Management KM is one of the key driving vehicles for the digital transformation . Digital data needs to be appropriately used considering the company s critical knowledge assets its. core competencies intellectual property rights market and industry comprehension and customer. understanding and expectations , KM is the art of transforming information and intellectual assets into enduring value for an organization s clients and its people The. core objective of KM is to provide the right information to the right people at the right times to help people share experiences and. insights and to improve the productivity of teams . With the help of technology businesses have developed robust software platforms to leverage KM strategies These software. continues to evolve in response to new demands and challenges Various data science techniques are being used to accomplish KM. objectives In addition recently there has been an increasing interest in how organizations can leverage augmented and virtual. reality AR VR in incorporating KM strategies in line with the objective of going digital . Businesses need to map the strategic and critical knowledge for complete digital transformation This helps in identifying those. knowledge assets that digital transformation can leverage as well as highlights gaps in an organization s knowledge network KM. prevents staff from constantly reinventing the wheel provides a baseline for progress measurement reduces the burden on expert. attrition makes visual thinking tangible and manages effectively large volumes of information to help employees serve their clients. better and faster KM in the current scenario is a necessary game changer . Hemant Joshi, Knowledge Management Big Data,Message from Confederation of. Indian Industry, The world of knowledge management has always been exciting with the move from data to information. to knowledge to wisdom holding out great promise for the future of companies societies and the whole. world Today the exponential search for new knowledge made possible by the proliferation of the. internet and smart phones and the dominance of the tech giants Alphabet Amazon Apple Facebook . and Microsoft has made it imperative for the science of knowledge management to lead new thinking. and opportunities for global transformation , The opportunity is not restricted to technology The world is seeing rapid advances of cyber physical. systems changing the processes of manufacturing distribution and logistics It is widely believed that. Industry 4 0 will lead to the digitization of all physical assets and integration into digital eco systems. with value chain partners McKinsey Co has called out four disruptions which make up 4 0 data volumes computational power. and connectivity business intelligence and analytics capabilities and human machine interaction advances like touch systems and. augmented reality Each of these disruptions has enormous potential for change in corporate thinking but together they create a. new knowledge the world will need new ways to manage the technologies processes data analytics and culture needed for people . companies and societies to compete and succeed in the future . Companies like DHL Walmart and Amazon are already practicing anticipatory logistics where demand is being forecast and. sometimes even created by intelligent suggestions to customers Artificial intelligence has a key role to play in this anticipation. process with the entire sequence of demand forecasting manufacturing transportation and storage planning and maintenance of. transportation equipment riding on the ability to use AI well and deploy machine learning to provide adaptive knowledge through. the supply chain Self learning logistics processes enabled by algorithms that recognize patterns and initiate action across the. logistics chain will enable dynamic changes in volume and timing of shipments inventory and stocking suggestions and pricing to. optimize product offtake and movement across the supply chain . The pace of change is disrupting old jobs and creating new ones As systems get more complex in every economic sector the. opportunities for human intervention in the design and implementation process will always exist and indeed grow The demand for. customer experience designers customer behavior analysts and new knowledge creators and disseminators will grow We are in. for exciting times and the winners of tomorrow will be those who use both human and artificial intelligence and machine learning to. build cognitive value chains in all industries KM practitioners of tomorrow will be at the center of digital transformation and must. prepare to lead ,Dr Ganesh Natarajan,Chairman CII KM Summit.
Knowledge Management Big Data,Digital Transformation through. Data and KM, Digital Transformation This spawned an entire generation of business opportunities using tools such. The usage of digital tools and tech savvy consumers who are adept as IoT AI ML etc thereby transforming. technologies to transform business in using digital tools for discovering themselves and their product factor. operations has steadily increased over products and experiences while also markets . the years While the earlier generation sharing instantaneous feedback through. of enterprise business applications such social media channels For businesses The key challenge for such. as enterprise resource planning ERP and brands such consumer technology organizations to harness the real. customer relationship management platforms are not only an important potential of digital transformation is. CRM etc helped digitize organizational distribution channel to invest but having an integrated strategy and a. data and streamline information also an important source of customer holistic approach towards Knowledge. flow within large organizations feedback providing real time insights Management KM in the digital context . advancements in technologies such in to the consumption patterns of their building internal systems and processes. as cloud computing cost effective products and services to streamline information exchange. communication systems and business and data analytics along with a. model innovations such as Software This intersection of digital technology strong culture of data driven decision . as a Service SaaS truly democratized across producer and consumer markets making Traditional KM practices and. the access of digital tools and made brought enormous amount of structured platforms focused on capturing and. them viable even for small and medium and unstructured data into the realm of codifying explicit knowledge in to. enterprises SMEs This eventually business operations which if harnessed digital artefacts making the collective. brought entire industry value chains into properly has a potential to transform organizational knowledge accessible. the digital fold enabling shared data business models generate new sources to the larger section of practitioners . flow and information exchange across of revenue optimize resource usage While KM practices and tools achieved. the supply chain such as producers and maximize stakeholder value considerable success across industries . suppliers distributers and retailers Successful organizations will be those more specifically in knowledge driven. thereby streamlining the delivery with a thoughtful and mature approach industries such as Consulting IT legal . experience and bringing efficiencies and to business process re engineering pharma life sciences etc they mostly. transparencies in the value chain As design thinking and technology focused on codifying explicit knowledge. data assumed center stage in decision assimilation to take advantage of such artefacts and providing search and. making this resulted in a virtuous cycle opportunities At the same time a strong retrieve capabilities to discover the. of increased investments in technology culture of a data driven decision making artefacts from the repository The. and data infrastructure and the vibrant is equally important to effectively missing element is the availability of. demand environment bringing down harness the power of data generate contextual knowledge with predictive. costs of digital tools further accelerating information and build knowledge and prescriptive suggestions which. their mainstream adoption across the Exponential technologies such as can connect the dots specific to. ecosystem Artificial Intelligence AI Machine the given problem and suggest. Learning ML Internet of Things IoT suitable solutions For organizations. On the other side commoditization Robotics etc provide more advanced to maximize the benefits of digital. of consumer technology and the tools to accelerate such transformation transformation this capability assumes. emergence of web scale IT systems and with their ability to collect and process significance as they now have access. e commerce platforms brought digital large volumes of data at a faster rate to large volumes of structured and. technology closer to the end consumers Digital first organizations having an unstructured data across the value. supported by contemporaneous integrated approach towards technology chain An efficient cognitive engine. advancements in smartphones and driven business operations are more supplementing the KM system that. the penetration of mobile internet likely to focus on new and emerging can gather meaningful insights from. Knowledge Management Big Data, the data and provide for a seamless to perform a task At the core ML solutions faster The value of such. discovery and delivery of contextual helps create a prediction engine for a tool increases manifold especially. knowledge to effectively address business applications that maximizes when the delivery of such contextual. business problems is the missing accuracy and minimizes errors This knowledge is seamless For example . element in the KM value chain which is achieved through experience as displaying indicative solutions when a. can enable organizations achieve the algorithms get exposed to more practitioner searches the enterprise. success with digital transformation and more training data and feedback knowledge base for a specific problem . ML could be beneficial for any AI enabled chat bots to help suggest. Knowledge Management and application that involves prediction suitable approaches etc . Artificial Intelligence such as medical diagnostics image. This is a domain where tools such as recognition autonomous driving AI ML can also help organizations. advanced analytics machine learning predictive maintenance drug discovery address the missing link in their. ML artificial intelligence AI and etc Whereas the focus of AI ML is knowledge flow which is in codifying. cognitive technologies could have towards building an accurate prediction tacit knowledge Traditional KM tools and. maximum impact1 Early developments engine to address specific business processes are very effective in codifying. in AI started in the 1950s and evolved problems the focus of KM tools is to explicit knowledge artefacts such as. over the years with progresses in help practitioners discover solutions operating procedures know hows . areas such as natural language through search and retrieval of the etc but fall short of brining the tacit. processing NLP text recognition codified knowledge base Essentially knowledge which is more unstructured. speech recognition robotics etc The AI ML and KM are two sides of the and people dependent to the benefit. field really took off with the advent same coin An advanced KM platform of the larger organization AI tools such. of machine learning ML and deep with a built in AI engine can bring as natural language processing NLP . learning which is teaching programs to contextual knowledge and predictive speech recognition text processing. learn for themselves rather than giving models for a business problem and can be beneficial in sifting through. them exhaustive set of instructions help practitioners discover effective unstructured data sources such as. Knowledge Management Big Data, emails community portals enterprise forecast by Gartner2 IT spending in constituency As programs such as. social networking platforms etc to India is projected to reach 87 1 billion BharatNet bring villages and remote. identify patterns and build a knowledge in 2018 which is 9 2 increase over locations to the broadband connectivity. map of the tacit expertise which can 2017 numbers While devices 31 4 network custom built KM applications. Knowledge Management amp Big Data Making Smart Enterprise a Reality March 2018 01 Knowledge Management amp Big Data Foreword 02 Message from Confederation of Indian Industry 03 Digital Transformation through Data and KM 04 Digital Manufacturing and Supply Networks 07 Customer Knowledge to Serve them Better 13 Learning and Skilling Data Empowering the People 18 About Confederation of Indian

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