Recently RELEX commissioned a comprehensive research project into the state of supply chain planning in the UK. The UK is widely seen to be a country that’s ‘ahead of the curve’ in retail supply chain management. The results were quite surprising.
Spreadsheets are still the primary demand and inventory planning tool for a significant proportion of the UK’s major retailers and the average age of the solutions used across those companies surveyed was 10.5 years – which, given the speed of technology development, is verging on the antique. However the market seems to be picking up, 39% of companies plan to replace their solutions. The majority of those that aren’t planning to do so can see the value of an update, but are put off by concerns about cost and the possible size and complexity of such a project.
I believe that we’re on the cusp of a change in attitude and that the combined availability of in-memory computing and SaaS will shake up the supply chain planning market. It is a view shared by leading technology analysts such as Gartner. Of course, as Gartner points out, the main reasons driving take-up of supply chain systems in the future will be that they both make the kind of planning we’re currently familiar with lots faster – results in minutes compared to days – and, even more importantly, they enable companies wholly new types of processes with a different level of planning detail.
I believe that we’re on the cusp of a change in attitude and that the combined availability of in-memory computing and SaaS will shake up the supply chain planning market.
Moreover in-memory computing and SaaS also overcome the current major hurdles that stand in the way of implementation.
Hurdle 1: Complex, long and risky implementation projects
Traditionally supply chain solution implementations have started with drawing up copious specifications and blueprints and have forced customers to make important decisions about their future planning processes at this very early stage – before the would-be users have had any hands-on experience with the new solution. In-memory-computing-based solutions, such as those RELEX and other modern supply chain planning solution providers offer, have changed the game in three ways.
- The computing power enables you to send all your data at the most granular level, which simplifies integration as you just need to extract raw data from your ERP or POS.
- The data modelling and planning levels can easily be changed whenever needed while using the solution. This makes the specification phase more fluid and enables the project leaders to make the important decisions with actual experience of how to use the solution in a real-life environment.
- Well designed in-memory technology enables both the user interfaces and business processes to be changed and amended on the go from the user interface as experience is accumulated. This further reduces the stress of the specification phase, and allows the solution to be fine-tuned precisely to the customer’s process needs at low and predictable costs.
For RELEX the combination of the way our technology works and the skill of our colleagues, who are experts in a range of supply chain planning areas, make projects fast and very low risk for us and our customers. Read more about how agile process development helps you avoid pitfalls.
Hurdle 2: Lack of investment budget for the implementation
SaaS is changing how companies buy solutions. The CIO of one of our customers put it this way: “Previously we had to think carefully about what was treated as an investment. It would be a ‘technology investment’, large sums would be committed up front, and it all had to go right for us to get a ROI in seven years. This is different. We can turn it on, and the solution flows like water from a tap. We can buy it purely on a business case – direct benefits for the bottom line. Later if we see those aren’t materialising we can turn the tap off and the cost stops with it. It makes it much easier to start.”
Previously we had to think carefully about what was treated as an investment. It would be a ‘technology investment’, large sums would be committed up front, and it all had to go right for us to get a ROI in seven years. This is different.
Modern vendors, with in-memory-computing-based solutions, can ensure their implementation projects are lean, flexible and predictable. This helps us because we can offer customers the chance to start with very limited up-front costs. We can get going quickly and go live in just a few months. From that point, even before the new solution is fully rolled out, the benefits of the improved process are already flowing and can be measured. There is actually normally no need for capital investment, as there’s no requirement for substantial advance funding and with ROI being achievable in weeks or a few months it means any investment is returned within the accounting period. In no time at all the customer has a new planning process powered by the new solution. The operation usually has lower operating costs and produces significantly better results. It is wonderfully uncomplicated to go forward when you know that you can see the actual benefits before committing to any investment. We also encourage our customers to test us from the outset with the most difficult challenges to see quickly how benefits are realised in those challenging areas. Read about our implementation with Booths and see the great results they achieved with their toughest challenge, chilled cabinet products.
It is wonderfully uncomplicated to go forward when you know that you can see the actual benefits before committing to any investment.
So, I predict with considerable confidence that in-memory computing will fundamentally change the supply chain planning market in the next few years. Partly because it enables a new approach with more added customer value, but to a great extent because it also eliminates the biggest obstacles to implementing a modern solution to replace old legacy solutions. I have to say that I am quite thrilled to be leading one of the companies at the forefront of that change.
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