In a competitive marketplace, vendors typically strive to position themselves against one another based upon perceived strengths. In markets with a superior and undisputed leader, the focus can devolve into creating competitive negatives.
In the Service Parts Management (SPM) market, the vendors who have had less time to develop software and less inclination to invest in research find themselves at a competitive disadvantage to Servigistics.
We have been developing purpose-built Service Parts Management functionality since 1990. With our commitment to thought leadership and the benefit of direction from the Service industry’s most progressive companies, we have engineered a solution with unequivocally deep functionality. This foundation, coupled with our subject matter expertise, allows us to incorporate leading-edge capabilities that leverage emerging technologies, such as IoT, Machine Learning, Artificial Intelligence, and Big Data Analytics. We are not just creating a parts planning tool, but rather, we are changing how parts are being planned.
Other service parts management vendors falling increasingly behind are curiously positioning their capability and vision gaps as an advantage by claiming to be “easier to implement and use.” They elevate the attractiveness of their simpler, less flexible, static offerings because they are simpler, less flexible, and static. In that context, Servigistics is labeled “complex.”
Let’s deconstruct what this means. Firstly, the proof is in the market itself. Servigistics manages the largest and most demanding global service supply chains. They represent the most complex supply chain challenges from which logically they would require the solution that best addresses that complexity. But does that mean the solution itself has to be complex? It is incredibly complex for the Operations Research Ph.D. to develop optimization algorithms that accurately represent the service supply chain's nuances or apply machine learning to sporadic demand.
Fortunately, the Servigistics end-user is insulated from that complexity as they deal only with its outputs, much like you follow your GPS directions without needing to understand the logic routing you. With hundreds of implementations in companies with wide-ranging maturity in planning, not one has ever come back and said that this is too complex to use. Complexity is a red herring, and if believed, it can be a trap.
The first issue of complexity is often raised about implementation. Some vendors claim an advantage in being able to implement more quickly with less introspection and decisions making. While that may be accurate, it is because you get it the way they wrote it, which may not be the way you want it. More importantly, that may not be how you want it when there are changes to your business that impact parts planning. It is axiomatic that flexibility breeds complexity.
By allowing extensive configurability in our solution, we deliver maximum flexibility to our customers. That flexibility requires more decisions to be made, which forces a thorough evaluation of as-is and to-be processes. Solutions that lack this flexibility allow the customer to avoid this evaluation of their future state but increases the likelihood of migrating the same outdated processes onto a new planning tool.
So a customer adapts to the vendor’s capabilities and limitations to define their process and strategy. What happens when there are changes to your business? What will you do when customers begin to demand binding Service Level Agreements (SLAs), or you expand your network into multiple echelons, and global theaters, etc. That vendor that was implemented because of perceived simplicity in implementation now has you locked into processes and strategies that no longer reflect your business realities and lack the configurability to adapt to the changes. Welcome to the world of workarounds and custom code.
The other reason that “simpler” solutions can be implemented more quickly is that there is less functionality to be considered. Breadth of functionality is a non-issue. All vendors must have basic capabilities in forecasting, stock level setting, supply planning, and reporting. The differentiation resides in the depth of functionality. The quick perusal of a vendor’s website noting the customers listed will give you a good idea of the service supply chains their solution can manage and is a powerful indicator of their functionality's depth. Supporting an F-22 fighter jet in a global theater is magnitudes more complex than supporting a power drill.
Why does this matter? Other vendors deliver maximum value potential on day one. Despite that potential being lower than ours, the point is that “this is all you get.” Servigistics’ layers of functionality provide clients with plateaus of future benefit as more and more capability is enabled over time. It’s like having all-wheel drive available for when Winter arrives. Complexity is a red herring.
What does “ease of use” really mean? Other vendors want you to think that it means the screens are clogged with so much data that users will struggle to comprehend. Ignoring the fact that this insults those very users, it is a humorously specious argument. Planning systems strive to resolve uncertainty in the supply chain and to increase the accuracy of their predictions and actions. The best practice is to bring as much relevant data to bear to resolve as much uncertainty as possible. Suggesting that the presence of this critical data is somehow an impediment to planning is a tough case to defend.
The expanded array of Servigistics features can take advantage of data others cannot, such as causal factors in forecasting. Therefore, more data is served up to the planner. Suggesting that there is an advantage in having less functionality, which uses a more limited data set, is laughable. How the data is presented is important. The Servigistics user interface (UI) has gone through rigorous end-user driven design sessions. Planners who want to take advantage of deep functionality have represented their preferences in how that data is presented. The extensive configurability of the UI allows users to reflect their role and their preferences in how it is presented. Complexity is again a red herring.
The last argument on complexity relates to the high-order math that we continue to inject into our solution. Competitors first try to claim that their results are “good enough,” and the marginal benefit of our admittedly superior math isn’t worth that effort. This has been consistently disproven.
For example, true Multi-Echelon Optimization (MEO), which only Servigistics can deliver significantly and demonstrably outperforms the competition in the ability to reduce inventory AND increase parts or equipment availability. When that approach fails, the argument moves to a claim that it requires a team of Ph.D.’s or data scientists to support and therefore will fail to deliver the value. It is true that the people charged with maintaining the parameters that drive MEO need to understand the fundamentals of supply chain theory. Admittedly, that is a skill all useful inventory planners should have too. And the people maintaining MEO only need to understand how to represent evolving enterprise priorities or constraints, e.g. budgets, in the MEO parameters, which is quite easy and extensively exercised in the model tuning during implementation.
The last ditch effort again is an insult to the planners, that they won’t be able to use the output from complex models like MEO. This is nonsense. To the planners, target stock levels are computed and used within the supply planning model with the results displayed in the Planner Worksheet. The end-user sees no difference in how the process is executed and how the results are presented to them, except that they are meeting their service levels with much less inventory. Alas, complexity is yet again a red herring.
So is complexity an issue? Yes and no. For us, as the vendor, we must deal with the inevitable complexity that arises from a solution that is predicated upon advanced data science and sophisticated algorithms and offers the maximum depth of functionality through the most flexible and configurable platform. The issue of complexity is ours, the customer and its end-users reap the benefits.
It all comes down to how you define the problem. If you define it as get me from point A to point B without having to walk, a bicycle and a car both fit the bill, with the bicycle being much cheaper. If you define the problem as, get me from Point A to Point B in the safest, most efficient way, in the least amount of time with the ability to alter my route for traffic or road conditions. You must then have the car and realize that the incredible complexity a car presents over a bicycle creates a huge advantage that outweighs any effort expended in learning how to drive.
Servigistics innovations in artificial intelligence, machine learning, big data, and IoT will optimize your service supply chain and unleash the full potential of your service business.