Several companies are now in the business of data warehousing. Enormous amounts of personal and official data is stored but not all zealously guard the information. Some companies have faced public backlash for their lack of proper data protection. According to a study by BCG, this data can churn revenues worth more than a trillion US dollars by 2020. This is because this data gets used in the business analytics process to unlock insights about customer use or preferences. But misuse can also render this data as dangerous. A lot of complex legal documents are written by companies so that consumers end up signing up for use of their data. Even those that are ethical end up stressing out their customers due to privacy breach issues. BCG advocates for misuse of data to be punished more strictly than a mere breach.

Source:https://www.bcg.com/publications/2018/bridging-trust-gap-personal-data.aspx?linkId=49448320

Uploaded Date:19 June 2018

Vineyard Vines was started by the Murray brothers who wanted to do something of their own, and not be tied to regular jobs. Its pink whale logo is now widely identifiable in the USA, with over ninety physical stores and similar success on e-commerce. However, the marketing technique is evolving. Over the years, the company has captured copious amounts of data on customer usage patterns. The data warehousing at Vineyard Vines runs into the terabytes. This has provided vital insights on business, enabling the marketers in the company to plan its campaigns more precisely. The digital marketing and communication that is driven by Vineyard Vines is now authentic, targeted and relevant. One of the key interventions this data-driven analysis and communication ahs done is to notify customers about stock replenishment during high demand-times. Last-chance offers are communicated for out-of-stock items. Special event and holiday-specific campaigns are run. There is also proactive identification of customers who may soon unsubscribe.

Source:https://hbr.org/2018/06/how-vineyard-vines-uses-analytics-to-win-over-customers?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert_activesubs&utm_content=signinnudge&referral=00563&deliveryName=DM7331

Uploaded Date:14 June 2018

Amazon already holds two-fifths of the online marketplace, but is growing at such a pace, that it will soon by 2021 cover half of it. But the Seattle-based e-commerce giant’s footprint does not stop there, as it has successfully expanded into several other businesses in recent years such as Cloud services, media, B2B distribution and hardware. This vast ecosystem means that Amazon ahs now become central to any due diligence effort made by Private Equity (PE) funds. The Amazon Factor as it is known also translates to a humungous quantity of data warehousing which allows for superior decision making. Such readily available data may be then used by PE funds for performing due diligence operations. According to a study by Bain, Amazon has the highest Net Promoter Score among top retailers across categories. The data advantage that Amazon provides also allows for detailed business analytics operations to be conducted. Future penetration can best be predicted using this as it tracks pricing, convenience to customers and return policies. For those doing due diligence tests, knowledge in each category is vital.

Source:http://www.bain.com/publications/articles/coping-with-the-amazon-factor-in-due-diligence.aspx

Uploaded Date:13 June 2018

A lot of companies today are locked in a conundrum. They are not sure whether to jump in and make use of business analytics, wait for the right moment, or whether their time has gone. The sooner, they get in, the better, especially in certain sectors. A study anchored by Bain has demonstrated that in retail and restaurants their revenues jump up by a factor of three, but in video distribution it is six times. In automotive, the jump is the highest at fifteen times. What is noteworthy is that though about seventy percent of all companies are using analytics, few consider it as their main tool for marketing or decision-making. There are broadly three patterns of digital disruptors in this field. Some get ahead simply because their services entail the least cost. These kind of firms exploit those with inefficient processes, poor resource-allocation and where the outcomes are low-yield. Then there those who deliver much better customer experience. They disrupt ones with slow learning, whose services offered are generic or priced excessively. Then there are the new business models which totally change the existing rules. They make extensive use of the vast treasure troves of data warehousing so their analytics are of highest standard. Their offerings are unique and the existing offerings merely turn into commodities.

Source:http://www.bain.com/infographics/analytics-disruption/

Uploaded Date:07 June 2018

Foreseeing a problem long before it occurs, and acting on it to prevent losses, is a fundamental principle of business. This is an especially acute problem in the smartphone industry which sees a lot of product-return within the free-return window. Though most customers claim that the reason for the return was the handset not working properly, research has proven that very often it is due to the user being unable to. There are manual methods to pre-empt this, by for example speaking to customers after they buy any product. There are some tools such as Best Buy Geek Squad or Apple Genius, but it is time-consuming. So, the best method is the use of business analytics using a predictive model. The intervention could help convert a potential returner to a non. An experiment on this will even reveal which intervention model will work best. The best part is that analytics these days leads to huge quantities of data warehousing. With each such operation, brands can always gauge which segments require max intervention and what methods are most successful.

Source:https://hbr.org/2018/05/using-analytics-to-prevent-customer-problems-before-they-arise

Uploaded Date:05 June 2018

Digital transformation is the buzzword affecting all sorts of companies. This is not a matter of concern at older, established companies, but also at digital native startups or unicorns. A perfect example of the latter is Uber which ahs moved on from being a taxi aggregator to a robotics lab looking to build self-driving cars. The term transformation is too vast, but one of the biggest impacts is on the people. That is why people analytics has developed as a unique field encompassing the tracking and analysis of data about traits, human behaviours and relationships. It seeks to displace anecdotal evidence, risk avoidance and hierarchy with data-backed business analytics, experimental research and forecasting. Microsoft’s Workplace Analytics division is a clear example of this drive. This team develops a baseline around which the efficiency of workers to adapt gets quantified. Traditional talent management techniques revolved around top-down strategic transformation. But in this evolved bottom-up cultural transformation, the how of things is given greater importance to the what. Tools have also been developed by Microsoft to monitor employee burnout. But ultimately it is not about the data presentation through charts or simply having more of this, but about the insights gleaned as best done by the people analytics field.

Source:https://hbr.org/2018/05/how-people-analytics-can-help-you-change-process-culture-and-strategy?utm_medium=email&utm_source=newsletter_weekly&utm_campaign=weeklyhotlist_activesubs_dalertnlsubs&utm_content=signinnudge&referral=00202&deliveryName=DM5946

Uploaded Date:01 June 2018

Not all companies get their business analytics program right. However, before passing on the final verdict on some companies’ success or failure in this regard, it is essential to look in to some clear signals that portend of trouble ahead. One such is when the executive team does not have a clear vision on how to use this information. Another is when there hasn’t been a feasibility study to assess the impact in the first year itself. The analytics strategy if at all is restricted to just a few use cases. The talent management in the organization is done poorly as individual roles are not clearly set, nor are future requirements. While the technical aspects of analytics do take place well, there isn’t enough done to ensure this data can be used towards solving real business issues. At such places, analytics emerges as a thing in itself, with a divorce from the actual business requirements. The analytics team or platform is then built without any end-result in mind. Even when decisions are taken to reduce the data storage, the clean-up efforts are way too costly and do not justify the effort. There isn’t any proper analysis of what real numbers are being generated by the analytics team. Finally, due to the neglect, there is no one dedicated to look after the ethical, social and legal ramifications of the entire process performed.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/ten-red-flags-signaling-your-analytics-program-will-fail?cid=other-soc-twi-mip-mck-oth-1805&kui=RjH_mljJLwlR6X3AUkOPrA

Uploaded Date:30 May 2018