As retailers seek to take every advantage of digital transformation, artificial intelligence is playing an increasingly larger role. In fact, the analysts at Global Market Insights forecast that investments in AI by the retail segment will exceed $8 billion by 2024. Retailers are experimenting with applications for machine learning, predictive analytics and deep learning technologies. And McKinsey & Company found that automation and AI will “fundamentally reshape activities and skills.”
Some retailers will experience quick wins and successful deployments, while others will struggle. If the latter group doesn’t see a rapid ROI, they start to feel that they’ve wasted their effort and resources. However, retailers can prevent this outcome if they understand in advance why AI and automation initiatives fail.
Here are five common reasons that AI-based automation initiatives fail:
- Unrealistic expectations
Vendors often paint a rosy picture of their automation solutions that create unrealistic expectations. Retail organizations are driven by trends and likewise, so are these companies’ IT departments. More and more, retail IT organizations are turning to automation solutions to stay relevant and keep ahead of the curve. An automation solution rendering benefit in one company may not benefit another, however, since each company has its own process and distinctive attributes. The success of an IT automation project also depends on meeting certain stakeholders’ expectations. These expectations should be clearly communicated and agreed upon by everyone involved.
As important as it is to understand the benefits of a solution or initiative, it’s just as important to understand its limitations. The use cases chosen should contain a mixture of operational and business benefits to sustain and generate tangible and intangible benefits.
- Treating automation like a cure-all
Automation isn’t a magic wand that can fix all issues. If automation initiatives try to automate workflows that are not currently working properly or undergoing change, the writing is on the wall. This is not only a waste of time and effort; it causes additional problems.
Before adding automation to the mix, leaders need clarity about their own digital and organizational environment. Deploying the solution onto an immature or outdated landscape and expecting to resolve the existing issues will result only in wasted time, effort and money. Establishing a long-term plan that addresses the internal problems first before applying automation on top can prevent this from happening.
- Lack of clarity
Leaders need to identify a problem that automation can solve. Then the tools and solutions, either in the organization or in the market, need to be thoroughly validated for long-term ROI. However, many times, organizations look to the newest and emerging technologies for the “wow” factor without really considering the full impact they will have. Those organizations that have been most successful with new technologies like automation and machine learning are those led by forward-thinking decision-makers who do their due diligence in assuring all key stakeholders are on the same page.
- Confusing the fundamentals
In most cases in which automation projects fail, the problem stems from diving too quickly into the “how” without spending enough time understanding the “why.” But the “why” is much more fundamental.
Without enough research and insight, leaders expect automation will be a “silver bullet” that will address cost reduction and efficiency gains. But that’s unlikely, largely because no solution is a silver bullet. Really digging into why automation is needed is essential and that starts with a good evaluation of the “as is” state. At this point, the gaps are examined and then the desired outcome can be agreed upon from there. Feasibility studies, ROI estimates and benefits timelines are critical before kickstarting any automation initiative. The key is to research and select a tool that is both affordable and scalable, bearing in mind the maintenance costs to sustain the automation initiative.
- Over-focusing on reducing headcount
There’s a tendency among the leadership to use job elimination as the yardstick for automation success. Scoring automation in this way is self-defeating and creates division among the non-automation resources. It is better to view the automation solution as an enabler to complement the team and free them up for real value-added activities.
A Successful Automation Mindset
AI and automation can be tremendous boons to retailers, helping to anticipate annual spikes in business, run real-time checks on store operations, monitor transactions for anomalies, reconcile inventory and much more. This will release IT teams to focus on higher-value tasks like optimizing systems to improve customer experiences. But assumptions and poor planning can quickly derail a retail automation project, so use the five points of failure noted above to create an initiative with a greater chance of success.
Akhilesh Tripathi is the global head of Digitate, a software venture of Tata Consultancy Services. He has been a driving force since the venture’s inception and is critical to global revenue generation and service delivery. Previously, as the head of TCS Canada, Tripathi drove the Canadian entity to be among the top 10 IT services company in its market. His 23-year career with TCS also includes his role as the head of enterprise solutions and technology practices for TCS North America. In that role, he led the management of strategic alliances with software vendors and participated on the advisory councils of several strategic vendor partners.