Mastering 2018 trends: It doesn’t have to be difficult

How to nail the “where to begin” and the “how to”

Mastering 2018 trends: It doesn’t have to be difficult

Happy New Year! I’ll be honest with you because we’ve grown close. Last month, I was going to write a blog post entitled “2017: A Year in Review,” which would’ve highlighted many of the biggest trends, breakthroughs, and best practices in the field of analytics over the course of 2017.

But in the spirit of analytics, I’ve taken a different approach: adopting a forward-looking view and entering the new year by not only telling you the most relevant analytics trends of 2018, but also practical ways that you can capitalize on them for yourself and your organization.

To be clear: this is not a trends list. We’ve already covered off on that. But this post is about what comes after that list. It’s the “where to begin” and the “how to.” Because while knowing the trends will help you have a great start in the new year, putting them into action is what will help you nail 2018. So, without further ado, the list:

1) Data management is more important than ever.

The trend: It’s no secret that data is making a comeback (like it ever left, amirite?). But it’s back in a big way — pun intended. While it’s just as relevant today as it was years ago, it’s become more complex. To get a full view of the customer, you now need to aggregate data across your digital analytics tool,
e-commerce technology, CRM system, marketing automation platform, order processing engine, predictive engines, intent data, product telemetry data, and much more.

How to nail it: If you don’t have one today, implement a Master Data Management (MDM) strategy. An MDM is achieved through a combination of process mapping, defining dimensions/measures/fields, systems architecting, and control mechanisms over the flow of data and information throughout the organization. But it’s not a one size fits all. What matters most is alignment, structure, and scalability. An MDM framework provides the technical structure needed to ensure data is being extracted, transformed, and stored in a stable, scalable way so that Foundational Data Models (FDMs) can be built.

If you aren’t creating FDMs, start in 2018. FDMs are centralized, sanctioned BI data models that include business logic, calculations, and application-ready data that can be used to launch multiple BI applications fast — we’re talking hours versus weeks.

2) The emerging role of the CDO/CAO.

The trend: I’ve mentioned before the important role a Chief Data Officer or Chief Analytics Officer plays in driving a culture of data-driven decision making at an organization. With analytics increasingly migrating from the IT organization into core business processes, the captain of that ship is the CAO. These individuals ensure that analytics is not an afterthought when making strategic decisions and is incorporated in all phases — from planning and brainstorming through execution and performance management.

How to nail it: Hire a CAO or a CDO. Might be easier said than done, but keep in mind that the actual title and level of the individual are less important than the role that they play. A senior leader who is a champion for analytics and dispatches analysts to all aspects of business operations is a fine start.

3) Data Security is no longer optional.

The trend: This one may not make some of the 2018 trend lists, but it’s going to be bigger this year than ever. Security is still a major driver behind the innovations of technology and data today. Cryptography is one of the primary appeals of blockchain technology. Cybersecurity is of primary focus given the Wannacry attack and the breach at Equifax in 2017. But in 2018, GDPR enforcement will warrant significant system changes, shifts in data processing procedures and guidelines, governance constraints, and failsafe mechanisms.

How to nail it: Run a security assessment to understand your vulnerabilities and risk factors leading to any exposures you may have to breaches or non-compliance with regulations. Consider data insurance. Routine risk assessment is a best practice that, unfortunately, many companies fail to do and end up paying significant amounts of money after data becomes compromised. If you aren’t sure if you’re prepared for the coming GDPR changes, perform a quick google search and you will find several free readiness assessments.

Here are some honorable mentions of emerging technology and patterns to be aware of:

  • AI. Artificial intelligence has started changing the way analytics is done. Predictive models and decision trees are still effective, but soon, neural networks, machine learning, and NLP technology advancements will create systems that churn through billions of rows of historical data to learn our businesses, industries, and competitors, and tell us exactly what decisions to make and when.
  • Self-service BI. Anything less than drag-and-drop data visualization is unacceptable. It is the job of the analytics team to not only deliver standardized data (ahem, FDM) but a governance and security strategy to get the right data to the right people.
  • IOT. The Internet of Things is one of the many drivers of big data. More and more wearable, mobile, and commercial tech will be generating data for businesses to increase their competitive advantages. Expect a rise in real-time analytics that displays data to users from their smart technology.
  • Cloud-based BI. The other benefit of increased regulation on data security will be an increase in cloud-based Analytics as a Service. More companies will leverage the scalability and mobility of having analytics in the cloud as concerns over data protection diminish.

Trends posts can sometimes be overwhelming. But this one should excite you. You know exactly which ones to focus on and what to do about them. One more prediction: you will read all of David’s blog posts this year (…can’t blame me for trying).

David Avery offers a forward-looking view of "where to begin" with your 2018 trends!

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