Beyond workload automation: Leveraging AI to improve IT operations in retail

Rahul

By – Somdipto Ghosh

(Senior Product Marketing Manager | Digitate)

The holiday season is almost here, and while the world looks forward to few relaxing weeks, for retail organizations it brings a period of high workloads, stricter SLAs, and high expectations to ensure zero downtime.
Managing peak demands of the shopping season have always been a tough ask for retail organizations, as it requires smooth co-ordination among the various moving parts across the retail value chain – including inventory management, procurement, logistics, store operations, marketing promotions and many other functions. Hence these functions have traditionally relied heavily on IT automation, specifically on workload management systems to help transfer and collate data across locations, update records, and perform a variety of IT functions on a daily basis.
However, each new season brings with it more uncertainty, increased workloads and expectations of performance as ever since the onset of the pandemic, consumer trends are changing faster than ever before, and local conditions have had a greater impact on on-site vs online sales for any given week. Most retail organizations are also expected to deal with several micro-peaks of specific items. It is now clear that existing IT Operations , especially workload automation strategies , need a re-think if they are to cope with the challenges of the upcoming holiday season.
Fortunately, AI/ ML models have matured to fulfill the IT Operations needs that go beyond automation, and workload management provides ample data and opportunities for AI based improvement. In fact , leading organizations are already investing in AI-based analytics to build more proactive processes for workload management. ignio™ AI.Workload Management has been a vital enabler in this regard for retail teams across the US, Europe and Asia Pacific, providing continuous monitoring, AI-based intelligence and predictive analytics. Here are few key retail needs that can benefit from the use of AI-based workload management :

1. Peak Demand Planning:

Due to the significant rise in volumes during the holiday season, most batch jobs associated with workload automation face increased demands. A failure to match up to the increased workload may cause delays and failures and result in missed sales opportunities. ignio can be used to predict the batch performance for a future date, with what-if simulations to assess the impact of a surge in volume. Retail organizations can use this to simulate the expected workload increase , and proactively plan for any improvements they need to make in the IT ecosystem to meet peak demands.

2. Managing perishable materials :

Perishable materials with low shelf lives are a particular concern during peak season, as organizations need to balance between wastage and the risk of products being out of stock. As per reports, any delay in replenishment of shelves often lead to shrinkage of about 40,000 perishable items and can impact up to 30,000 transactions per month due to out-of-stock products. Organizations also run short-term promotions and discounts on perishables, to ensure maximum sales, whenever there is excess stock. ignio can help in ensuring that daily reports on sales and stock are generated on time, giving enough time for decision making. It can also provide continuous monitoring and remediation of the batch ecosystem responsible for ordering, distribution, and stocking of perishable goods, ensuring smooth business processes.

3. Ensuring smooth supply chain

Peak season pushed the demands on the entire supply chain- from procurement of stock items, to storage in Distribution Centers (DC) , to daily allocation and replenishment of stock items for each store. In retail organizations with hundreds of stores across geographies, this is both difficult to plan and monitor daily, more so as the work is distributed among different IT systems, each with its own infrastructure and job schedulers. ignio aids the smooth functioning of all these processes with a single pane of glass view of batch jobs across different IT systems, and autonomous monitoring to find anomalies in any process. It also provides intelligent alert management – ensuring only the business-critical alerts are provided to the IT team, with enough lead-time to ensure timely resolutions.

4. Roll-out of discounts and promotions

Peak demand brings the chance to build new loyal customers, along with the risk of losing existing ones. Retail organizations need to be agile to act on the market sentiments and internal stock limits, and roll out effective promotions and discounts quickly to compete during this time. While timely BI reports can help them strategize, it also need to be implemented quickly on the ground, which requires on-time price tag generation, printing of signage and ensuring a consistent POS experience that is updated with information about daily discounts and promotions. ignio plays a key role in the timely execution of the batch jobs of each of these processes, providing the necessary agility that the team needs.

As the rate of digitalization of retail operations increases, so too will the dependence on workload automation to keep the business running at the back end. Traditional automation-focused IT strategies are useful but there is a need to look beyond just automation to build resilient IT operations. Retail functions can now benefit from AI-powered workload management, and by leveraging ignio, retail IT teams can prepare for long term improvement in their processes.

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