Seven keys to the future world of big data

in Industry Insights, Technology, 04.04.2019

For organizations in every sector, grappling with the new world of big data has presented huge challenges. Firms are rethinking their strategies, rewriting their business models, reacting to new regulations, implementing new technologies, and seeking to onboard different competencies. Our team recently attended Big Data World 2019 in London, where industry leaders explored these themes and more. A few major areas stood out in particular, which we, together with KPMG Lighthouse, have outlined in this article. Read on for seven keys you’ll need to unlock the world of artificial intelligence, machine learning, and more.

Don’t dismiss artificial intelligence

AI is here to stay: the industry understands its importance and wants to embrace it. The question, of course, is how. It begins with rethinking operations along the entire value chain, updating business models or developing new ones, and then finally exploring and piloting AI tools. Some organizations remain cautious of AI, given the opaqueness of the underlying technology and other regulatory concerns—but, overall, the momentum is strong towards an AI world.

Plan for higher risks of failure

Projects that significantly involve machine learning tend to have a higher failure rate. There several reasons why, mostly to do with inaccuracy and incompleteness of data, risks inherent in any newly introduced technology, and overestimation of the AI capacity. Interestingly, another common pitfall is a lack of deep understanding of this technology from the executives running the business. Indeed, it is not yet the norm—it was estimated recently[1] that only one CIO out of twenty-five is successfully using AI currently.

Define your strategic plan

Setting clear goals within a defined strategy is more important than ever. Successful AI initiatives those that are supported by top management, and operated by savvy technical personnel who have the proper resources and skills. Such initiatives also maintain a strong commitment level and a perpetual mentality of improvement. To mitigate the risk of failure, plans should be broken down into manageable and deliverable chunks.

Be agile and learn from others

Now is not the time for thinking that is overly narrow, or for decision-making slowed down by too much red tape. A successful business transformation will require a fast pace, lots of quick learning about new technologies, and careful observation of experiments done by industry leaders.

Consider outsourcing your infrastructure

Infrastructure-as-a-service (IaaS) is flourishing. How come? Simple: it’s cost-effective and fast to operate, and it decreases the risk of exploring new technologies. It is expected that more and more organizations will adopt IaaS in the near future, given that it enables them to cope with daily workloads without the hassle of buying, managing, and supporting the underlying infrastructure.

Put your head in the cloud

Cloud-based software-as-a-service (SaaS) is rapidly growing as an enabler of innovation for many companies. SaaS facilitates the development of proprietary software and allows you to experiment with new ideas more easily and safely.

Don’t give in to the buzzword mania

Terms like big data, machine learning, and artificial intelligence are everywhere at the moment, from news articles to boardroom discussions. As happens with buzzwords, the definitions of these terms are often relaxed into general concepts rather than specific meanings. This, however, can cause issues in strategy-planning or hiring: for example, the label of “data scientist” is frequently misused, leading to mismatches between profiles and jobs.

This article was prepared together with Oliver Zlotowski.

[1] Gartner recently cited this statistic at Big Data World 2019 in London.

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