Experience to make sense of business challenges as if time will stand still and technology implemented over a couple of years will help what is now a two-year old prob- lem. In my book, these types of projects are business as usual. To use an analogy, you don’t win at a game because you focus on winning, you focus on the best team, fundamen- tals and teamwork—a way of achieving a sustainable level of performance, which you then adapt as circumstances require. Any changes you make toward achieving that higher level of sustainable performance, is transforming. Under- standing that technology/innovation are accelerating is like understanding the fundamental rules of the game. And the basic rules are no time outs and the games will keep accelerating at a faster pace. In order to be truly successful, your orga- nization must be prepared to continually adapt. This requires a sustainable infras- tructure (platform) and an adaptable organization (people), which will provide process and can quickly pivot. The Rate of Acceleration is Accelerating Innovation, connectivity, and data are piling on top of each other at faster and faster rates. IDC estimates that by 2025, collectively, we will have 175 zettabytes of data, and that is growing at a doubly exponential rate. Likewise, we will see acceleration of technology at combina- torial rates with many new business models, going far beyond product development to affect every aspect of our social and economic lives. When it comes to harnessing the power of product data – and data in general – across the product lifecycle, recognizing this fundamental truth of acceleration is what separates the winners and losers. You are either a data disruptor or you run the risk of being left behind. The increased spend in digital transfor- mation is a reaction to the acceleration of business disruption. Unfortunately for many established organizations, by the time they have agreed on a response to an opportunity or threat, it is too late—a disruptor has changed the game. You cannot move at a glacial rate when dis- ruption, too, is accelerating. 2020-1 ProductDataJournal 39 Rethinking PLM in the digital age (Image source: Getty Images) field. This is driving the need to manage these assets with up-to-date configured Digital Twins. These Digital Twins are individual configurations of physical products or systems of assets and pro- vide the context you need to create value across the lifecycle. The Digital Twin tracks all of the changes to the asset as it exists in the field and, at its core, is comprised of an as-maintained Physical Part BOM, which allows you use the Digital Thread to provide traceability back to CAD models created in Engi- neering, simulations as well as service bulletins, work order history, IoT data, historical data, electronics, wiring, soft- ware, firmware and then continuing back to the systems architecture and require- ments including parameters such as soft- ware settings. But, the product ecosystem expands beyond the firewalls of the OEM. To compete more effectively, companies must continually optimize their supply chain to allow for greater collaboration, more innovation, and driving time and cost out of their products. This too is increasing the scope of the product ecosystem. Many companies are feeling the effects first hand of having to dynam- ically change suppliers. Digital Transformation Throughout the Lifecycle We’re in the midst, of an industrial and cultural revolution—not just because of emerging technologies, but perhaps even more so due to the acceleration and sheer volume of data. In addition, the acceleration of connectivity is caus- ing not just our product ecosystems to expand in every direction, but organiza- tionally and socially as well. Clearly, we’re becoming more connected. To get a handle on this and avoid disrup- tion, companies are investing in digital transformations. According to IDC, digital transformation spending will reach $2.3 trillion by 2023 (IDC, 2019). The problem with spending trillions on digital transformations is that up to 70% of them fail (McKinsey, 2019). ”Through 2021, digital transformation initiatives will take large traditional enterprises, on average, twice as long and cost twice as much as anticipated” (Gartner, 2019). The reason they take twice as long, and cost twice as much, and still ultimately fail, is they are based on a linear mind- set. A transformation is not about a singular project with a start and end date. You can invest heavily in technology (IoT, AI, Big Data, AR/VR, Fog, Edge, cloud com- puting, etc.) and fail miserably. This has been proven time and time again over the last few years. Executive sponsor- ship, a huge budget and focusing on your most pressing business problem is also no guarantee. The fundamental point behind any trans- formation strategy is to recognize that technology (and innovation) is accelerat- ing. Therefore, the key is to transform to a place where you have a sustainable way of adapting. You are essentially improving your ability to react to what hasn’t occurred yet. Unfortunately, most decisions are not based on non-linear thinking, so we try