A year in review 2018
Blog: End to End BPM
In 2018 I saw the rise of the ecosystem and the commoditization of the IT platform. The IT platform still continues to be the first step or the common denominator to enable digital transformation. It brings interoperability in hybrid models that provides the foundation for not just an Internet of things, but an Internet of things, people, and services working together as well as new kind of technologies like mixed reality and cognitive services by bringing together human, machines, and artificial intelligence. It allows to process the complexity of machine-generated signals, large amounts of customer data, with better and faster analysis of product performance and reach. Nevertheless, a business ecosystem, gradually moves from a random collection of entities that interact or transact to a more structured community, adding more partners, more products, more offers and enlarging the customer base. Of one key success of Amazon is how they grow in terms of product offerings. They started as book store. Today, they sell virtually anything. In business ecosystem, a company manages information and its flows. In terms of data, this is not about our view of customer, that can be expanded how each partner that belongs to ecosystem increases that view of the customer and how it detects new opportunities by having access to a bigger customer based and detailed customer profile customer profile, because data is shared with other companies together. Companies will monetize from each transaction occurred as all the other connected partners, the more the customer buys, the ecosystem grows as the business opportunities. On the other hand, this will allow to evolve business capabilities. If a highly efficient logistics company – that manages a fleet X fold in size and it is serving a wider customer base – joins the ecosystem, all the merchants may if they want, benefit from the new innovative added capability, if you attract fintech to support new ways of doing payments, they will drive new interactions with millennials or digital savvy customers. In a business ecosystem, companies coevolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the next round of innovation.
In online retail, vertical e-integration is a new paradigm. e-commerce players are already expanding their own brand business into more categories. At the same time, specialized start-ups are selling products such as razor blades or functional foods directly to consumers, often on a subscription or membership basis. By bypassing distributors, these start-ups are able to offer lower prices and sell even small volumes profitably. The music industry is a great example. Today, artists are posting their songs directly onto internet-based music platforms, and in the process avoiding consolidators, distributors, and intermediaries of any kind. Internet of things, edge / fog computing like connected product – toothbrush, kettle, toaster or appliances, can create new business models and revenue models as it is happening with household appliances. Audi, just released an electrical SUV (e-tron) which the new revenue source is selling electrical energy to charge the batteries that will be billed the customer later.
In manufacturing, new digital operational model are being deployed under the cyber-physical systems concept. Which is the fusion between operational technology and information technology, data created by the manufacturing equipment, the warehouses, the trucks that deliver the final products, the signals broadcast by the smart packages, that allows to manage a network of factories across multiple locations, in terms of being adaptable in real time managing manufacturing capacity, based on customer’s orders or comparing performance and expanding continuous quality improvement circles based on the data that is made available from the shop floor. The hype related with self-healing systems is a reality. Instead of humans constantly fine tuning machines when product is being produced out of specification, it is possible to implement runtime procedures that will act on machine parameters when it is predicted that quality specifications will be missed. Using Machine Learning combined with IoT to understand how an equipment operates and how to fine-tune it’s operation to become more efficient or to ensure product quality features, to start to prescribe machine interaction in terms of automatically recommend actions in terms of machinery parameters if it is necessary to put product features back to specification is also being part of the shop floor digital journey transformation. Despite there are challenges related with data interchange, low latency access to cloud services, there is progress with the emergence of each asset, each machine, component is able to initiate an exchange of data to different levels of the organization ensuring integrated, planning, control, execution, optimization of the value chain, this probably one of the most silent areas which progress is not being reported, but I see finally some real value apearing and being materialized.
2016 entry can be found here – I did not write in 2017 about this.
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