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The role of digital technologies has been well documented by several publications and reports. But one area where the impact of big data has been underscored is the global food chain. At every level from the farms to the plate, food companies can harness this data to create sustainable solutions. There are several steps in this overall journey, beginning with innovating at speed using soil sciences. This must lead to holistic input optimization. Farming operations then need to be optimized. The supply chain will automatically become more transparent thanks to the presence of data points across the journey, connected digitally. Downstream operations have to be stepped up to improve operational efficiency. There will be infrastructural challenges along the way, especially in emerging markets such as in Africa. Business analytics can help identify these bottlenecks in infrastructure before providing ideal warehousing location inputs using geospatial model. Once the cycle is completed, the supply chain company must anticipate waste. Granular data needs to be collected for this from waste streams before proving solutions from the retail level onward.

Source:https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/how-big-data-will-revolutionize-the-global-food-chain

Uploaded Date:10 November 2018

Professional social networking platform LinkedIn has now launched Talent Insights. Developed by Microsoft, Talent Insights is a business analytics tool to identify talent. This simply reiterates the importance LinkedIn is paying to human resources software. The tool will provide real time insights on people. It will help managers engaged in talent recruitment and retention. To help such professionals, LinkedIn creates a Talent Pool report which will break down the performance of employees as well as potential candidates across factors. These factors include location analytics, attrition rates, workforce planning and product management. This suite is not yet directly a competitor to SAP Success Factors or Workday. But once usedcombo with Microsoft Dynamics, the results are formidable.

Source:https://www.zdnet.com/article/linkedin-launches-talent-insights-for-hr-analytics-talent-planning/

Uploaded Date:09 November 2018

Today there is very little excuse for businesses not to make use of data for their decision making. This is true for both consumer-facing as well as B2B firms. The head of digital marketing at Google says that this approach will soon replace the HiPPO bias. HiPPO stands for highest paid person’s opinion. This usually means the opinion of the CMO or other such high official, whose opinions are based one experience and gut feeling. This might work out on a number of occasions, but won’t many times. The healthcare industry is making use of data for its decision-making, but few players are able to make the right use of business analytics. Instead of using data as a transformational force, many are simply using it as a defense mechanism towards their confirmation bias. As a result, data and its subsequent analytics is only taking place retroactively, after a project is done. This allows for analysis, but remain postmortems. But those shunning HiPPO will go a step ahead and proactively weed out deficiencies for the next projects.

Source:https://www.adweek.com/digital/how-re-evaluating-data-analysis-can-transform-a-brands-reach-and-engagement/

Uploaded Date:08 November 2018 

The Senior Vice President at Genpact spoke about how his company has been proactive about business analytics since a decade back. Digital-led innovations and digitally-enabled intelligent operations are what the company is focusing most on now. Genpact has even consulting assignments in the airline industry where the knowledge of analytics was needed. Their Bind Ratio solutions has been well adopted across industries. Gnepact is now expanding its talent pool for news assignments. One really exciting one is with some universities with whom they have tie-ups on curriculum development. Corporate training is a key part of Genpact’s outreach now. They have a programme to raise the ‘digital quotient’ of its employees worldwide. There is even an Anlytics Academy to bridge the industry-academia gap. Within India, Amrita University, Manipal Global and BITS Pilani are some of their key tie-ups. Both technical and domain expertise is to be built up through such exercises.

Source:https://www.analyticsindiamag.com/genpact-incubated-an-ecosystem-to-identify-develop-nurture-analytics-talent-a-decade-ago-says-sudhanshu-singh/

Uploaded Date:08 November  2018

The last few years, this realization has dawned among most companies, that there must be proper data warehousing for all the data that the company generates for the purpose of analysis. Germany-based ZF was one such, but several startups had started eating into their share, so there was a fear of the company’s “Kodak moment”. ZF realized it needed its own lab dedicated to business analytics. Steps were thus taken in the right direction. After a few stumbled, it worked as ZF focused on the right internal customers. The high-impact problems got identified. For this proper storage of the hard data was needed along with efforts to motivate the team. This led to the right execution. Fortunately for ZG, there was able support from the top executives. External perspectives were also collated to get an unbiased view. Domain experts were enlisted within the services too and empowered. As a result, the ZF Data Lab is now working in fine shape.

Source:https://hbr.org/2018/11/how-a-german-manufacturing-company-set-up-its-analytics-lab?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert_activesubs&utm_content=signinnudge&referral=00563&deliveryName=DM17944

Uploaded Date:08 November 2018

The use of business analytics is now so much steeped within most organizations, that managers can no longer afford to not know about it. Some concepts have been identified which even non-data or analytics experts must have some idea about. It starts with randomized controlled experiments. One needs to be proficient at data warehousing to get this started. Another such tool is A/B Testing which is considered as almost necessary in the research process. Regression analysis is the next, with the linear method being the most commonly applied one. There exist detailed and easy-to-use statistics programmes to conduct such analysis. The last one is statistical significance. This is the art of understanding what stat is truly important and what kind of data to use to gauge authentic business insights. All this and much more has been described in the book Data Driven: Profiting from tour most Important Business Assetwritten by Tom Redman.

Source:https://hbr.org/2018/10/4-analytics-concepts-every-manager-should-understand

Uploaded Date:06 November 2018

By now it is well-known across the business spectrum that sales performance can be improved drastically by making the right use of business analytics. It can be used in several ways such as to improve the pricing mechanism and subsequent discounting when needed. The forecasting accuracy improves thanks to the availability of top-notch data in large quantities to be processed using algorithms. Due to such data-enabled customer insights obtained, the customer churn is usually lesser as brands are able to act on what is needed by them. Selling has historically been considered as an art, but the science part of it is increasingly creeping in. For this science to succeed, one has to ensure that the data being used is clean, non-pilfered. The sellers must be empowered with the right solutions. They must know when to make use of which application suite. But to ensure that all these ends are met the right people are needed. So, the talent recruitment has to be geared towards finding inquisitive and tech-savvy personnel.

Source:https://hbr.org/sponsored/2018/10/power-sales-performance-by-harnessing-analytics

Uploaded Date:06 November 2018

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