Got 99 Problems, but Data Availability Ain’t One: How Asset Tracking Data is Shifting Towards Problem Solving
By Tancred Taylor |
04 Jun 2021 |
IN-6189
Log In to unlock this content.
You have x unlocks remaining.
This content falls outside of your subscription, but you may view up to five pieces of premium content outside of your subscription each month
You have x unlocks remaining.
By Tancred Taylor |
04 Jun 2021 |
IN-6189
The Open Visibility Network |
NEWS |
While uptake of asset visibility technologies is still in very early stages, the ecosystem has developed to the point that visibility and numerous data points are readily accessible to enterprises that understand their potential value. Devices, platforms, mapping services, and location services—to name but a few components of the full solution—have reached levels of technical proficiency and price points where they are no longer major roadblocks to adoption. One common complaint, however, is the ability to execute on the extensive data captured by sensors and trackers. A commonly touted figure is that only around 10-20% of total ingested data is analyzed in such a way as to produce valuable and actionable insights and outcomes. Visibility is already possible, but the greatest value of visibility comes from what problems an enterprise is able to solve with that data. This is where traction is gaining in the asset tracking market.
Roambee’s shift towards becoming a ‘signal’ company exemplifies the shift. A signal is abstracted and analyzed sensor information, augmented with third-party data sources, and fed as an actionable insight. In other words, the value comes less from the raw visibility data fed into a platform, but from the understanding an enterprise can derive from that data when it is put in context and analyzed. In early May 2021, Roambee enhanced their capability to deliver analytics and insights through their acquisition of Arnekt. Another important example is the Open Visibility Network (OVN), established by Tive in February 2021. Founded together with supply chain visibility leader project44, the network has since expanded with a number of additional members such as FourKites, TransVoyant, and Everstream Analytics (with the latter two joining in early May). The goal of the OVN is to share data and encourage collaboration to provide the best visibility for end customers. The idea is that an enterprise can use their single chosen platform to visualize their own operations, as well as gather data from their upstream or downstream suppliers and vendors, who may be using alternative platforms by enabling two-way communication via an API. The understanding is that data from all parties is readily available; that data collaboration enhances the value to the end customer; and that the value a technology supplier can provide is on the advanced applications and analytics.
Moving Beyond Visibility |
IMPACT |
These developments mark a transition from an enterprise’s concern about how to get data from its connected assets and processes, to a concern about how to use data to optimize processes and performance. This idea of advanced analytics, in particular predictive or prescriptive analytics, is by no means new. Sensitech, for instance, a leader in connected loggers and real-time trackers for the supply chain, has been in this game for a while, driven by its acquisition by Carrier back in 2006 and a combination of acquisitions and in-house product development since then. The company states that it focuses on visibility beyond temperature, with a holistic approach to “good cold chain management” more broadly. Numerous other platforms, software companies, and system integrators of all shapes and sizes also exist to aggregate data and provide applications and analysis.
The novelty now lies in the timing and open industry collaboration. On the timing front, a broad ecosystem of device makers and supply chain visibility providers has developed, with a number of these companies starting to scale and experience some form of consolidation behind their solutions. As the ecosystem densifies, as more devices get connected, and as more data makes its way onto platforms, the potential value of using the data for broad process changes across an entire supply chain increases significantly. These advanced analytics require vast quantities of data, both from sensors and from various assets or vehicles within the supply chain, as well from third-party integrations. The prevalence of numerous types of connected devices performing a variety of functions (whether tracking, monitoring, or otherwise sensing) in an increasingly digitized supply chain infrastructure means that these data points are much easier to acquire.
Despite the timing, consolidation, and the growth of bilateral partnerships within this ecosystem, there are still substantial visibility gaps within supply chains because of the use of different technologies (or the use of no technologies): this is where open industry collaboration can help bridge the differences. As a result of the consolidation within the ecosystem, leading platforms like FourKites, project44, Shippeo, and others are here to stay. While companies may be able to compete with each other to improve their own product offerings, either through in-house development or through strings of acquisitions (as has been seen recently—such as project44’s acquisition of ClearMetal and Ocean Insights, FourKites’ acquisition of Haven, or Descartes’ acquisition of Portrix), offering the best solution to an end-customer requires visibility into both upstream and downstream suppliers. The challenge has been with siloed businesses and platforms preventing this end-to-end supply chain visibility and enabling access to all of these—either through open APIs to an existing system (as with the OVN), or through a separate piece of software, as with chain.io (which acts as the ‘plumbing’ between all supply chain platforms)—significantly improves the level of visibility in supply chains and enables enterprises to start solving much broader problems or challenges. Supply chain technology providers have understandably been very possessive about the data they gather, but there is an increasing shift in thinking about what the product is: it is less the data as it is the applications and ‘signals’.
Agoraphobia: The Fear of Openness in a Greenfield Space |
RECOMMENDATIONS |
In summary, the OVN provides more data and greater transparency to enterprises, enabling them to take broader decisions on their operations, as well as enhancing the possibilities for future supply chain collaboration on the customer front. This may take the form of truckload collaboration between suppliers (seen in some instances on a small-scale or bilateral basis, such as Coca Cola with Colruyt and Van Dievel, using CHEP’s transport collaboration solution to reduce number of empty trucks and empty miles), optimizing delivery schedules, or reducing risk—among numerous other possibilities. While the benefits are clear on the customer front, much of the roadblock has come from the technology supplier front due to fears around sharing data that is increasingly considered a company’s primary asset. There is a greater responsibility on the technology supplier in providing this openness and non-siloed approach, and the asset tracking technology ecosystem is increasingly coming to terms with this approach. As initiatives towards openness and collaboration develop, solution providers must be able to overcome their possessiveness over proprietary data and adapt their business models to reflect this, with the central focus of providing the best possible product and services to their own customers. The growing OVN represents a new form of ‘coopetition’ and is one of the first steps towards breaking down silo barriers in supply chain asset visibility, and towards facilitating bilateral or unilateral approaches to data sharing. With the openness and ready availability of data going forward, the focus on product differentiation will increasingly come down to the analytics and applications. The data is increasingly present: the real challenge for companies is how to use this data and existing systems and technologies to address their problems.