As I’ve said before, the biggest challenge facing supply chain and logistics executives today is not managing change, because that’s always been the norm in supply chain management, but managing the rapid pace of change. Customer expectations, regulations, the competitive landscape, technology — all of these things are changing so rapidly, companies having a hard time keeping up; their existing technology, talent, and decision-making processes can’t keep up with this rapid pace of change.
Therefore, successful companies of today and tomorrow need to make smarter decisions faster. The two key words here are smarter and faster.
Smarter means better linking planning and execution processes, which many companies have been talking about and trying to enable in various ways throughout the years, but have not been able to fully realize due to technological limitations and other challenges.
Smarter means taking a truly holistic perspective across the supply chain, across functional groups and trading partners, and across strategic, tactical, and operational planning horizons.
When you look at the potential benefits in inventory savings, freight savings, and on-time fulfillment improvements, it’s not that difficult to build the business case. So, what’s been the problem?
A key constraint has been speed. Simply put, if companies tried to optimize orders, inventory, and transportation simultaneously, across thousands of SKUs, the optimization models would either break down because they couldn’t handle that level of complexity or the solve would take way too long (many hours or even days), which would make the effort impractical, especially if the goal is to tightly link planning with daily execution.
Therefore, the manageable approach has been to aggregate SKUs into groups or categories, and to optimize orders, inventory, and transportation separately, with planners making manual adjustments afterwards to balance the outcomes. While companies have achieved some level of success with this less granular and siloed approach, they also recognize that they have been leaving money and process efficiencies on the table.
So, what’s changed today?
Over the past few years, we’ve seen great advances in modeling/optimization technology and approaches, and equally important, cloud computing has greatly compressed processing time by several factors, so we’re now at the point where Closed-Loop Operational Management is possible — that is, where companies can tightly integrate planning and execution processes and create a feedback loop to drive continuous improvement. Instead of aggregating SKUs into groups and optimizing in silos, companies can take each SKU into account and optimize orders, inventory, and transportation at the same time, to make smarter decisions faster — i.e., instruct the execution systems how to allocate, what to order, when to order, and how to move goods through the pipeline, while considering real-life operational constraints.
So, what does Closed-Loop Operational Management look like in the real world? In a recent webcast hosted by Logistics Management and sponsored by Solvoyo, I had the opportunity to interview Orhan Dağlıoğlugil, Chief Operating Officer at A101 Stores and Levent Hatay, Board Level Advisor and Former CEO at Vestel to share some insights from their implementations.
I encourage you to watch the webcast to hear them tell their stories directly, but here’s an overview of A101’s case study.
A101 is a discount retailer that sells high-quality, cost-effective food and consumables throughout Turkey. The fast-growing company (60% year-over-year sales growth, with $1.5 billion in sales in 2013) has 3,200 small footprint stores and 20 regional distribution centers. A101 has 900 regular SKUs and 2,000 total active in its stores, so each day across it network, the company has to make more than 3 million replenishment decisions.
A101 faced a familiar problem for many retailers: not having the right products, at the right time, at the right stores (even though the company was replenishing its stores three times per week). This lead to high inventory carrying costs at some stores and out-of-stocks at others. The underlying issue was inaccurate sales forecasts from the stores, which were not detailed enough, coupled with a manual planning process and the fact that demand varied by store and region.
Therefore, A101’s goals were to reduce lost sales due to stock outs; provide the right mix of display merchandise, shelf stock, and safety stock to its stores; and provide store managers with a system to place replenishment orders more efficiently. Working with Solvoyo, the company implemented the Closed-Loop Operational Management process depicted below:
Mr. Dağlıoğlugil describes the process in more detail during the webcast, but in a nutshell, the Solvoyo solution determines the optimal inventory profile considering demand, sales targets, open and in-transit orders, and display constraints, and then sends replenishment recommendations to each store manager’s hand-held device for approval or adjustments if necessary. Once approved, the optimized inventory replenishment plans are uploaded to A101’s store execution system for store order fulfillment.
The net results: A101 decreased store stock-outs from more than 10% to less than 5% (with a margin contribution of $1.7M); realized annualized inventory savings of $8.1M; and opened 130 new stores with no additional inventory investment.
The bottom line: Closed-Loop Operational Management is not a new concept; companies have been striving to take a more holistic and integrated approach to supply chain planning and execution for many years, but they were limited by existing optimization technologies and computing power. Advances on both fronts, especially the rise of cloud computing, now make Closed-Loop Operational Management possible, and early adopters like A101 Stores and Vestel are showing what’s possible when you adopt it.