It is well known that today organizations and platforms are generating enormous amounts of data. In fact, analytics, artificial intelligence, internet-of-things and big data are now among the most talked of aspects. However, utilization of such data depends more on the firm’s management rather than technology. Thus some methods have been separated out which must be the primary aim of such operations. First of all, this enormous data must be used for better decision making. Innovative products, processes and services need to be developed. Data must get imbibed into every aspect as information needs to get extracted from different products, processes and services. This business intelligence garnered must be used to disseminate relevant content to concerned stakeholders. There must also be a method where one can be directed towards the right content as Google and Quora are already doing. The overall quality must be improved, costs eliminated altogether and a sense of trust developed. Asymmetries get built in when one party has more information than another. Such asymmetries need be leveraged as a business proposition as done by several hedge funds, car dealers, sports venues and airlines.

Source:https://hbr.org/2017/06/does-your-company-know-what-to-do-with-all-its-data?referral=00563&cm_mmc=email-_-newsletter-_-daily_alert-_-alert_date&utm_source=newsletter_daily_alert&utm_medium=email&utm_campaign=alert_date&spMailingID=17463422&spUserID=OTY0OTMwNTk5NwS2&spJobID=1041158494&spReportId=MTA0MTE1ODQ5NAS2

Uploaded Date:01/07/2017

Machine learning leverages Artificial Intelligence (AI) for digital transformation. By the year 2025, this along with related technologies could be worth a hundred billion US dollars in the market. There are several ways however using which machine learning is helping companies improve their work processes. As a first, customer service is getting improved by making use of chatbots. Machine learning is helping gauge real time authentic business intelligence on customers’ traits. This is further enabling their individual characteristics to emerge so personalized marketing can be possible, enhancing their loyalty levels. A lot of mundane, repetitive jobs are getting automated, with highest positive impact being felt in finance, enabling the professional from the field to focus on high level strategic tasks. Such automation also helps reduce manual fraud through early detection. Talent recruitment has also improved as algorithms can cut across vast swathes of data, thus eliminating clutter. Similarly, this analytics can also be used to assess the overall brand exposure. A lot of data can also predict upcoming business trends, market needs and forecasts. Even supply chains are now smoother due to better developed algorithms. Other areas, where machine learning could soon further improve operations include Drone or satellite induced asset management, career development and assessment of retail shelf lives.

Source:https://hbr.org/2017/05/8-ways-machine-learning-is-improving-companies-work-processes

Uploaded Date:27/06/2017

Chief Marketing Officers (CMOs) have unique challenges these days propelled by innovations such as cloud computing, business analytics, social media, smart phones and gigantic heaps of data. That is why it is important for them to prioritize functions and realign the company’s focus in that direction. First of all the disparate streams of data from different sources need to be interwoven together to derive cohesive meaning. The data warehousing operations done must deliver customer value. This will help in providing relevant solutions to the customer base. Costs are being controlled by leveraging social, mobile, analytics and cloud technologies as has been done by Cisco. Instead these investments like events and tradeshows are being driven towards training the people or new technologies such as on automation or loyalty programmes. Habits also need to be modified accordingly. For example the content needs to be tailored specifically for the relevant audience rather than mass campaigns. Data needs to be replicable to be a success in overseas markets as well. The CMOs can no longer simply allow the CIO to provide all technology support as marketing has becoming increasingly driven and not just reliant on technology. The CMOs needs to understand basics of data security.

Source:http://www.forbes.com/sites/onmarketing/2014/04/29/why-cmo-leadership-is-essential-to-data-driven-marketing/#2215e1261555

There is clearly a greater need to streamlining the operations between the sales and marketing teams. Data powered business analytics is one such tool. The Chief Marketing Officers (CMOs) do not require to intervene at all times if there are proper reporting procedures in place. A dashboard must be constructed specific to the company where the analytics will detail the entire marketing efforts and sales achievements in summary form. This will help the CMO to weed out any differences between sales and marketing teams. Due to the vast data warehousing operations that most platforms maintain these days, analytics can eke out predictive analytics. This will assist marketers in predictive the next moves of individual customers as well as the overall market. Similarly, even practical analytics can be evoked from them such as analysis on each of the campaigns and what went wrong. It can even be used to engage on social media or in CRM related tasks.

Source:https://www.martechadvisor.com/articles/bi-ci-data-science/three-ways-data-analytics-can-foster-greater-alignment-between-sales-and-marketing-teams/

Due to the massive hype regarding Big Data, companies are scrambling to capturing such data and making use of them. So that it moves on from mere hype to actually rendering results, some strategies have been worked out. First of all, the data bottleneck has to be eased out. A typical problem is that companies employ small teams to crunch massive quantities of data. However, by the time, they have finished their business analytics operations, the resulting analysis is of little value as the data is now quite old and new events have since taken place. To fight this conundrum, companies must create a sense of data urgency among everyone, so all can chip in. There are several software available to aid this process. Also, marketers must explore newer questions and not just use the analysis to get answers to existing questions. The entire organization must collaborate so that the final analysis is worthwhile to all. Collaboration is much easier now thanks to platforms such as Slack, Microsoft Teams or Facebook’s Workplace.

Source:http://www.forbes.com/sites/forbestechcouncil/2016/12/27/how-to-unlock-the-value-in-your-companys-big-data/#2e42bcb56e70

Big Data and its analytics is playing a major role in enhancing productivity in the USA. It is enhancing customer experience by collecting genuine insights on the customer before disseminating it among the service providers. This helps customers get exactly the service they desire and providers can pinpoint their deliverables. Traditional businesses are getting transformed as they now have deep business intelligence that was earlier lacking on what customers need. Wal-Mart and Capital One for example have been able to improve their operational efficiency by eliminating redundancies and thus increase sales as well as turnover. New businesses have also been generated such as ITA software that optimizes data for airliners and then further sells them on to travel agents and websites.

http://www.techbullion.com/big-data-analytics-improving-innovation-productivity-usa/

The airline industry historically has been amongst the least profitable. At every chain, there exist other vendors who take away the bulk of the incomes. That is why as the oft repeated maxim says, “necessity is the mother of all invention”, airlines have constantly strived for business innovations simply to survive and grow. In terms of technology, decisions support systems and use of data, airlines have always been the pioneers. Now strategic partnerships are being forged with car rental companies, OTAs (Online Travel Agencies), airports or analytics firms simply to leverage the world of collaboration. The concept of loyalty schemes also emanates from airlines’ frequent flyer programmes. Now the focus has also gone towards business analytics which crunches enormous quantities of independent social media data. WNS has been at the forefront of this trend by analysis this data, both social as well as otherwise to provide business insights. The airline industry in general has always had a customer-centric approach which is why such data crunching will provide information to further improve the service provided to customers.

Source:http://knowledge.wharton.upenn.edu/article/leveraging-customer-analytics-the-airline-industry/