This article describes how a new ecosystem in supply chain software has emerged, combining end-to-end (“Best-of-Suite”) and specialized “Best-of-Breed” products. We also touch briefly on how Best-of-Breeds can stand out and grow in such an environment.
We’ve seen interesting development lately in the realm of Enterprise supply chain software.
Usually, the goal for the manufacturing client is to have one go-to platform / reference solution combining a proprietary database, calculation engines and a versatile User Interface (“End-to-End”).
From there, the End-to-End idea is to cascade the effects of a change at one point of the chain, for example in the demand, to the other layers. Depending on the way in which the supply chain is organized – and what the specific competitive advantage of the manufacturing company in question is – the organization is dominated by a pull methodology (make to order) or a push methodology (make to stock).
In most manufacturing groups, S&OP processes (for Sales & Operations Planning) are designed to arbitrate those forces, in keeping with the company’s north star, and End-to-End products from top software providers incorporate dedicated S&OP modules. Plus, some sort of “Control Tower” proposition comes with an End-to-End product to monitor it all.
Complementary to those core End-to-End enterprise offerings, several specialized “Best-of-Breed” start-ups have started to gain traction with many large manufacturers. Examples include S2-Data (truck loading optimization), Quantics (forecasting), Pelico (factory operations management), Sphera (assessing supply chain disruption risk) and our company GenLots (operational purchasing), just to name a few.
While the largest software vendors flesh out their “Best-of-Suite” offerings, as mentioned in the intro, they can’t replicate the diversity, speed and creativity of “Best-of-Breed” software products, therefore leaving large niches open.
Combined with the rapid acceptance of cloud architecture by large manufacturing groups this creates the perfect conditions for a new type of ecosystem, where larger, established software vendors collaborate with up-and-coming players. The former gain in terms of upselling possibilities (especially for their cloud propositions) and client satisfaction/retention, while the latter gain from the increased exposure and to some extent from presence of an existing infrastructure/database that they do not need to manage.
Nice symbiosis. There is a catch though. 3 catches really, for a Best-of-Breed start-up to stand-out and benefit from this symbiosis. Let’s look at them in detail and show concretely how those obstacles have been addressed by GenLots, which optimizes operational purchasing – i.e. purchasing patterns of every material used in industrial production – with proprietary AI.
- There are hundreds of products out there competing for the attention of operational excellence teams. Therefore, financial impact must be immediate and obvious.
At GenLots we can calculate our projected impact on the companies own data and immediately give an estimation of the savings potential in case of implementation. This impact is always a 10%+ reduction in inventory, order costs and sometimes even purchasing price.
- As large manufacturing companies already manage a maze of supply chain software layers, they must rapidly acquire the conviction that they cannot obtain this impactful business result through their existing applications. This is very hard as a lot of applications in Supply Chain achieve similar sounding results – i.e. inventory reduction – in different areas or through complementary means. Often technical knowledge has to be very deep and detailed to understand if there is overlap.
As GenLots, we established partnerships with existing players such as SAP to clearly demarcate our solution from their existing offering, getting the weight of their internal experts to insist that the way we are reinventing MRP, a process which has not changed for 40 years, is completely novel and not on the SAP roadmap. The avenue to growth is therefore one of collaboration instead of competition.
- EVEN IF business results and uniqueness are clearly established, the perceived effort to install and run the new product NEEDS to be low – all the more when working with organizations which have yet to design “fast tracks” to integrate cloud-based technology and are not yet cloud-native.
As GenLots we started last year to offer a complete “API-Only” offer.
Whereas before, the GenLots User Interface was quasi-mandatory, we now provide a more lightweight and integrated version which achieves every IT-leader’s dream: zero change management + integration through configuration of existing infrastructure (rather than development).
Avoiding these three pitfalls will grant a strong USP to supply chain start-ups selling Best-of-Breed Enterprise software products. When it comes to the next stage, growth, 5 main strategies can be observed for them to thrive and reach objectives such as USD 100 M. in yearly sales.
- Going from Enterprise to Mid-market.
Assuming the technology is equally impactful on mid-size companies, distributing a compact version of the product to this market segment is a viable strategy. It is also assumed that experience gained from serving large and complex clients makes working with smaller organizations easier. Channel partners might have to be adapted and client acquisition going from primarily outbound to a mix of inbound and outbound. Ex: Celonis and process mining (“Enterprise grade but not enterprise only” is one of their slogans).
- Going transversal – If the product is differentiated but also sufficiently transversal, you can be in the envious position of having a product so specialized to a specific problem, that the problem doesn’t change between industries.
GenLots typically works very similarly whether in heavily regulated Pharma or fast moving food and beverage. You still have to market differently to the different verticals as benefits might be quite different, but you can use the same technology, same channel and go for the same segment (Enterprise) to corner what ends up being a very large market.
- Expanding through controlled diversification (“verticalization”), i.e offering other modules that are adjacent to the existing proposition within the supply chain stack.
This can be a good solution to increase loyalty and price point but it comes with a caveat: the diversification has to leverage efficiently the initial technology sold, otherwise there is the risk of losing focus. Underappreciated by start-ups is that you will be competing in new categories with more established solutions and have to defend multiple positions at once. Ex: Colibri, from S&OP to demand planning and forecasting.
- Specializing within one industry vertical.
Orienting a software product to specialize in a specific industry can increase the technical advantage, as well as the price point and the dependency. Ex: Inato – which specifically facilitates clinical research studies.
- Adapting the business model.
Switching from a pure SaaS model to a mix including more professional services. Ex: Jaegger, from source-to-pay software to a full fledged consulting company.
The complexity of modern supply chains is such that there isn’t an excess of supporting software out there: Best-of–Suite software vendors traditionally aim to offer End-to-end products addressing several key supply chain activities (including Enterprise Resource Planning, Warehouse and Transport Management Systems, Forecasting, Demand Planning, Supply Planning and Sales & Operations Planning) but more specialized, Best-of-Breeds offerings emerge to complement these propositions.
Manufacturing groups can now create agility and efficiency for themselves leveraging both. Large vendors create marketplaces to facilitate adoption of their specialized cloud partners.
To distinguish as a Best-of-Breed technology provider, you need to make sure that the technology is impactful, unique, and effortlessly activable.
Once that is done, current eco-systems present a plethora of growth strategies to build a robust cloud business.