Closing the Gap: 5 Factors for Successful AI Adoption

robot-human-handshakeEasy is better, easiest is best they say. Who’s they? Consumers.

Consumers demand convenience.

This is what it really boils down to –all the change shaking up the retail industry. Consumers want it now, easy and free.

[T]he battle for convenience is the battle for industry dominance. […] Convenience is one-click, one-stop shopping, the seamless experience of “plug and play.” The ideal is personal preference with no effort.” The New York Times

While the retail industry is disrupted by consumer preference for convenience (without a doubt), it’s also disrupted by the evolving technologies in place to deliver on these new expectations. We already know what the consumer wants, but how do we actually go about delivering on these needs? How difficult is it for businesses to adapt?

Data Transformation in a Data-Driven World

Data-driven transformation is the key to delivering on consumer expectations in today’s digitally-powered world.

According to Gartner, the rise of data transformation arrived as a result of businesses realizing the “strategic importance of using data to achieve mission-critical priorities” through “more innovative data-driven insights and decisions, achieved by using analytics.”

Why is that? Because we have loads of data available! Everywhere.

It only makes sense for businesses to leverage the data at hand to keep up with the evolving market needs and demands.

Artificial intelligence and machine learning technologies are growing more and more in today’s business environment (beyond just retail!) because they literally run on data—it’s the fuel to their engine which allows businesses to leverage information about consumers effectively and efficiently as ever.

In Comes AI Adoption

For the reasons described above, AI continues to receive a lot of “hype” given its influence and disruption across various industries. The potential for change is undeniable:

“The convergence of AI, robotics and the IoT, together with mobile, social and big data, will transform current retail business models and organizational structures. This will revolutionize retail during the next few years.” – Gartner, Predicts 2018: Retail Unified Commerce Will Require Even Greater Collaborations and Alternative Models for Success

Nonetheless, many industries (like retail) subject to its disruption are unable to keep up as they are fundamentally rooted in old, traditional business models and systems.

Transforming your business organization to leverage these innovative technologies is no simple feat. The whole process is far from simple, considering a handful of misunderstandings about artificial intelligence persist and the quickly evolving nature of such technology.

It’s a significant undertaking, both financially and organizationally. Data-driven transformation comes with its own set of challenges, in addition to the existing problems they’re meant to solve.

It’s changing the way things have been done for years. With that being said, it ain’t easy.

So how does one go about adopting AI successfully? 

At last month’s Retail’s Predictive Analytics Forum, Bryan Eshelman—Managing Director at AlixPartners—provided five tips for introducing data-driven business transformation in today’s data-driven world: 

  • Tip #1: The Zealous Advocate

It all starts at the top. But you need more than just simple “buy-in” from the management team. In order for action to take effect, executives seriously considering AI implementation into their business processes must act as evangelists for transformation to really take root.

  • Tip #2: Press On, Again and Again

The process for driving such drastic change in an organization requires perseverance. There is no “silver bullet” solution, unfortunately (oh we wish there was!) for introducing this type of adoption. It requires time, constant experimentation, and persistence to find the right topic, partner or team to effectively manage expectations for AI implementation.  

  • Tip # 3: A New Mentality 

The old way of thinking is long gone. We are in a new era, where data rules all. For that reason, it’s necessary to break away from the “how things were done and have always been done” mentality and inject a different way of thinking. In addition to incorporating this ‘outside in approach,’ it’s even more important to strike a balance between your data team and your current team when adding related tasks to their ‘day job.’

  • Tip #4: Quick, Discrete Wins

Leverage data-driven solutions to tackle discrete, actionable problems with near-term results. The key here is using quick wins to fund further investments into the technology. 

  • Tip #5: Track Your Progress 

Lastly, ensure you’re keeping tabs on performance and results using the right tracking tools and metrics. Take advantage of digital dashboards to track progress and align results with a repeated use of metrics to build familiarity. With this, you can present results to drive accountability for performance over time.

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Topics: retail technology, artificial intelligence, inventory optimization, machine learning

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