But is Analytics over hyped now, is there more talk & less action on the ground. There is a need to take a closer look at analytics: in the years to come blind belief in data analytics will change & a more serious look at what analytics can truly deliver will now begin to form.

The US elections have shown that you need to know the limitations of data as well. Nate Silver famously called two presidential elections nearly to perfection: He got 49 states right in 2008 and all 50 in 2012. But he was way off the mark with Trump in 2016! Even he said recently after the US election results: “We’ve learned that we have to be careful about how we convey uncertainty.”

If you are a company thinking about either starting out in Analytics or scaling up your analytics practises, it may be a good time to think & plan for 2017. Thanks to the hype that Analytics generates, organisations have bought into the concept, but many are still unsure how to “make it happen” for them.

Here are some of the trends that I see for 2017

1. The democratization of data: More data is now available to companies of all sizes. And thanks to solutions like Amazon Mechanical Turk, businesses will be able to much more easily collect data from around the world which they previously did not have access to. So more easily data within a company & sources to find external data will be a trend that I see growing larger in year 2017.

2. Data Infrastructure Should Become a Profit Centre: Companies that start treating data as an enterprise wide corporate asset will be able to create new revenue streams. This will need sensitivity to customer’s personal identified information.
3. Companies will share data through mutually benefiting data exchanges : Data’s value increases when it’s shared. Sharing data allows marketers to better understand who their best customers are, which consumers they should market to, and with what specific offers.Gartner Predicts 30 Percent of Businesses will Be monetizing their Information Assets directly by 2016. Companies that create data sharing ecosystems, will benefit in following ways:
• The data you receive in return adds valuable marketing perspective that you probably can’t get on your own. As a marketer in M&M,a Mahindra XUV customer also owns products like Mutual funds & Savings accounts or has service relationships like DTH or Telecom.
• Sharing data helps transform your channel relationships from transactional into long-term partnerships, which can fend off price competition and open doors to other co-marketing activities.

4. Ability to tell stories: Analysts need to “Story tell” to embed analytics into the fabric of the company. But analysts are too one-dimensional & not embracing the intersection of “technology, statistics & business”. So analysts struggle to tell stories. Often I see journalists do a far better job with infographics in media. But information journalists are not wanting a career in analytics & so there is a gap. Story telling is not the same as pretty charts. Visualization’s are being commoditized. Amazon and Google have both released near-free offerings that offer their users basic visualizations. I see analysts will become more effective in telling stories using new age tools or platforms.

5. Growing importance of the User experience: The customer experience for analytics users will continue to be very important as more & more business users start to use Analytics systems. Advanced analytics is no longer just for analysts.
6. Using analytics & Big data for improving Customer Experience: Customers will demand value for their data. They will be willing to share their data , if the exchange is fair. And improved customer data will allow companies to hugely personalise the customer experience.

7. Marketers can help customers lead a better life: Whatever business you are in, customers will want you to add value to their lives. Helping customers use their own data in creative new ways can be a great differentiator. Customer data can be used to benchmark customers. Customers would love to know how their telecom spends compare with someone of a similar profile. Am I spending too much time on the phone lately, that too in my personal hours on official matters!Or how many hours of Kids television does my household watch as compared to others. Customers may willingly provide more data(information about their family’s or interests) in return for getting value addition like this.
8. Mobile adoption creates exciting possibilities: Given the massive shift to mobile shopping, companies will need to develop a mobile-led omnichannel strategy rooted in a “mobile first” mind-set. Research shows that 25% of Mobile apps are only used once and 58% of users churn in the first 30 days of using an app. Mobile app analytics would start to include a lot of geospatial analytics. With businesses accumulating more and more data on their customers’ locations and corresponding activities, it is necessary for decision makers to generate insights that include this information to increase customer loyalty, sales and other outcomes. The use of automation and Artificial Intelligence within mobile app analytics will also be a game-changer. More in-depth analytics centered around uninstalls. Examining the causes of uninstalls can play a vital role in user retention.

9. Companies will build massive Customer single view : Companies will start to merge data across systems keeping the customer at the centre of it all. You need to be able to merge Mobile app data, sales data, marketing data, service and support data, and potentially other kinds of data into a single unified whole. In order for companies, from key executives to customer service reps, to best make decisions and interact with their customers, they need a wholistic view of analytics from all customer-facing platforms. This does not exist today & companies will use the engineering developed by new age companies like Facebook & Google to create such infrastructure.

10. Analytics will depend even more on company culture: As companies look at Analytics to give them a competitive edge, they need to make key changes in their information technology, their structure, their processes, and their culture.Culture is absolutely key to analytics adoption. You don’t often hear about a close partnership with HR for analytics adoption, but it is critical for culture change to start. I think in 2017 you will start to hear about this more often.

11. Companies will build Creative analytics team: Bring together a team of people who are integrators & who come from the intersecting skills sets of statistics, technology & business. Analysts should not think about their job as purely high end geeks, rather they are story tellers who help make business impact happen using data. Think creatively about staffing this team-bring a journalist, tech geek & stats jock together in one group & see the magic.

12. Younger people will disrupt: Analytics will move towards being a far younger person’s game. Average age in online business is far lower. Younger people are adopting analytics far faster. They are getting exposed to it in their education & they are consuming it through their “digital avatars”. They see this often as a “no brainer”. Older executives are harder to convert to this line of thinking.