Transparency in companies, publishing dashboards to everyone to keep everyone updated of the progress and not being able to adjust data can be scary for some people. A BI fail in a large corporation, we often consider faulty process or management to be the reason but it might be due to lack transparency between managers, board members and shareholders. Managers always refer to preferring  accuracy over speed, but accuracy takes months to implement so managers tweak the data which makes it useless. Nowadays, new generation managers are politics free and depend on technology and SaaS apps for improvement and speedy delivery of data. They don’t mind sacrificing 100% accuracy to 80% if they can get the job done 5-10 times faster. Read more at :

http://www.business2community.com/business-intelligence/dark-side-business-intelligence-01845255#7ot2lqmRUYVhQfAj.97

Analytics help retailers move to a unified commerce experience and allow for more targeted, cost-effective marketing. Advanced analytics is used for the optimization of merchandise planning. Real-time analytics is integrated with customer and product information across all channels. Retailers have the ability to use science and algorithms to optimize pricing strategies to reduce markdowns, improve demand forecasting to optimize inventory, localize assortments and optimize space planning. Advances in software and the occurrence of cloud-based solutions enable retailers to think about accelerating their upgrade/replacement cycles. It will help limit overstocking and discounting. With real-time analytics, retailers can market to consumers on a 1:1 basis based on customer context. Retailers have the ability to know what customers have in their closet, purchase behavior and preferences. For more, read the article written by Forrest Cardamenis : 

http://www.luxurydaily.com/analytics-offer-solutions-to-merchandising-and-marketing-problems-brp/

Customer service is the most effective part of any company. It not only helps to improve customer retention rate, but also helps to understand new market trends. Big data analytics and business intelligence play a crucial role here. Simple web crawling into a social site helps to understand the on-going sentiment and current market trend. Different social responses, video hits, ads and newsletters help to optimize the search results. In other word this process facilitates smother recommendation system and customer centred predictive modelling. To make a better prediction we can use –

1. Connectors help to integrate diverse data sets in different formats

2. Lightweight search facilitates even non-technical data analysis

3. Queries optimizes the search dynamics

4. Enterprise search also scores with its semantic search, which means that the context is recognized and included in the analysis and structuring of the data.

Using all these parameters business enterprises can design a better profitability model.

To read, follow: http://www.computerweekly.com/blogs/Data-Matters/2016/02/search-driven-business-intelligence-intelligence-for-a-customer-centric-business-world.html

Like others, retailers also require advanced analytics to compete in the digitalized marketplace. With the expansion of Internet of Things (IoT), the effect of multichannel retailers will increase as they will start using advanced analytics. Advanced analytics, the analysis of data kinds using sophisticated quantitative methods that produce insights unlike the traditional approaches to business intelligence (BI).  These advanced analytics tools put information in the hands of business analysts and business users offering significant potential to create business value and competitive advantage. The need to improve real-time business decision-making will force retailers to acquire self-service and big data discovery capabilities. Read more at: http://www.analytics-magazine.org/special-articles/1352-retailers-need-advanced-analytics-to-compete-in-the-digitalized-marketplace