{"id":14038,"date":"2017-12-15T14:42:27","date_gmt":"2017-12-15T13:42:27","guid":{"rendered":"https:\/\/timoelliott.com\/blog\/?p=14038"},"modified":"2017-12-18T17:04:35","modified_gmt":"2017-12-18T16:04:35","slug":"why-analytics-will-be-at-least-4x-more-important-in-2018","status":"publish","type":"post","link":"https:\/\/timoelliott.com\/blog\/2017\/12\/why-analytics-will-be-at-least-4x-more-important-in-2018.html","title":{"rendered":"Why Analytics Will Be At Least 4X More Important in 2018"},"content":{"rendered":"

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At the recent Gartner Data and Analytics event in Frankfurt, analyst Rita Sallam\u00a0predicted\u00a0that \u201canalytics will have an even bigger impact on society in the next twenty years than the internet did in the last twenty.\u201d<\/p>\n

\"\"<\/a>The incredible growth in machine learning and artificial intelligence, in particular, is set to remake every facet of today\u2019s society and redefine every business process.<\/p>\n

But even without taking those sweeping changes into account, I believe that analytics\u00a0will\u00a0at least four times more important than ever in the coming year. <\/p>\n

Here’s why:<\/p>\n

1. Faster innovation cycles<\/h3>\n

The core purpose of analytics has always been to support executive decision-making — according to Gartner, analytics remains the most important technology priority for companies around the world, as it has been for most of the last decade.<\/p>\n

But decisions are more important than ever. In today\u2019s fast-changing markets, the future belongs to agile companies that can adapt quickly. Having the right insights at the right moment, and being able to act on them \u2013- in other words, having effective analytics — is increasingly the difference between survival and extinction.<\/p>\n

2. From a process-driven world to a data-driven world<\/h3>\n

In the world of analytics, we\u2019re used to processes creating data that we can use for analysis. But now data is being used to create processes for digital transformation. In these new digital processes, the different steps are constantly changing based on real-time information and algorithms.<\/p>\n

For example, think about customers buying products. In the old days, this was a fairly linear process: I might see an ad, say, then go to a store, and make a purchase. But now we live in a much more complex, omni-channel world. The most advanced companies are optimizing the end-to-end customer journey using real-time analytics at every point of interaction \u2013 steering customers to the best outcomes: \u201cIs the customer profitable? Should we offer them a discount? What other products might they be interested in?\u201d, etc.<\/p>\n

The result is that every customer is essentially following a unique, personalized process, powered by data and analytics. And these processes change automatically as the data changes, making them more agile and flexible, and more suitable for today\u2019s fast-moving markets.<\/p>\n

And it\u2019s not just the customer experience that\u2019s changing \u2014 all modern business processes, including human resources, logistics, finance, and manufacturing, are now constantly being adjusted and optimized, on the fly, based on real-time data. Analytics moves from being separate from “operations” to being an integral part of it.<\/p>\n

3. Analytics is\u00a0part<\/em> of the products and services that you sell<\/h3>\n

Companies are moving from selling products to creating experiences, and data is an essential part of that process. Whether it\u2019s an estimate of how long your Uber will take to arrive, or the quality of a book recommendation from Amazon, or the ability to analyze your B2B invoices, data is increasingly a direct part of\u00a0your customer experiences, and what you use to differentiate from your competitors.<\/p>\n

This means that your product managers need to be able to experiment with data in new ways, testing and iterating these data-based experiences for your customers.\u00a0This\u00a0relies your existing analytics platform, but it\u2019s about using data for top-line growth rather than bottom-line efficiency, and requires\u00a0more creative, flexible self-service than in the past.<\/p>\n

4. Direct data monetization<\/h3>\n

It\u2019s now\u00a0easier than ever to monetize information in new ways, turning information more directly into income.<\/p>\n

You have been gathering vast amounts of information to run your business better \u2013 but others may be able to benefit from that information, too. By aggregating, augmenting, and anonymizing information, you can sell it in new ways to new customers \u2013 creating new business models based directly on your data. Data from retailers can reveal deep insights about brand choices. Data from telephone companies can estimate footfall in front of retail stores. Providers of contingent labor can tell you the average salary differences between data scientists in Palo Alto and Bangalore.<\/p>\n

What you should do next<\/h3>\n

Digital transformation<\/a> means data is more important than ever — here’s how to get more from your existing analytics investments:<\/p>\n