While the world struggles with its most severe pandemic in 100 or so years, the key underlying dynamics of enterprise success have not changed. Enterprises need to move even faster and become even more agile to not only survive but also thrive during the pandemic. Practically this means CxOs need to tap into digitalisation, leverage the new infinite computing era, build differentiating next generation applications, and above all, practice enterprise acceleration. Finally, software becomes the key trait of an enterprise’s DNA, determining how well an enterprise will fare in dynamic times.
CxOs need to look at the three fundamental mechanisms of any enterprise:
• The supply chain. CxOs need to figure out how they purchase and procure services and goods. Digital marketplaces, software agents and more are the key feasible innovations.
•The value chain. The way enterprises create their value add to deliver attractive products and services has been massively disrupted. It has to be reset all the way on how people work together, collaborate, and be rebuilt and reinvented as fast as possible.
• The demand chain. What enterprises can sell to who and how is continuously changing with technology. A simple web store is not enough. To win, enterprises need to listen to prospects and customers, make mass customisation real and become omni channel virtuosi.
Besides the three chains, the other determinants are the key resources of an enterprise – assets, finance, and people. With enterprises struggling to keep their business going special consideration is given to capital as it is the essential component to invest in the way forward. Offices and data centres do not look like the best idea to CxOs these days, especially when they see relatively low utilisation. The once humming and cost-effective mainframe running reservations and more at an airline looks like a massive CAPEX dump – at 10 percent utilisation. Same for office buildings. Wonder what the five year ROI of Apple’s shiny new campus will be?
How COVID accelerates the move to cloud
Experiencing the CAPEX crunch, CxOs look for any way to find methods of operating the value chain that ties its expenditure to the performance of its overall business. If the enterprise grows, it pays more for resources, if the enterprises shrinks, it consumes less and therefore pays less. That is where the cloud as a platform becomes so attractive, as its core nature of elasticity allows exactly that – the expansion and contraction of computing needs as the enterprise requires them to power its value chain.
But there is more than the technology, elasticity must find itself also in commercial terms, enabling commercial elasticity, resulting in lower bills on lower usage. Naturally, cloud providers are flexible with upward elasticity, but not in all cases with downward elasticity which equates into less revenue for them. Many first-generation SaaS vendors still operate their own data centres, effectively coming up with the CAPEX to operate them. On the other side, a SaaS vendor who runs on other clouds, can offer more flexibility in commercial terms. As user demand ebbs, technology consumption ebbs and with that costs. Effectively the cloud vendor who operates its
cloud data centre is stuck with the CAPEX bill. Now, SaaS vendors that can isolate themselves further by leveraging a platform vendor, that by themselves sits on another cloud, are even more and better isolated. Finally, being able to operate on a cloud platform with non-enterprise loads gives both SaaS vendors and their enterprise customers the best isolations in the post pandemic roller coaster economy.
Understanding the key concepts
By now you have a good understanding of cloud and its inner workings. But what about the other key technology concepts – here is a short rundown:
• Infinite computing. If you cannot count something, it may as well be infinite. Even better if you can pay for it as your busines scales up and down. The end of finite computing that relies on sized machines in your data centre is the start of the infinite computing era. Its five layers are already familiar (infinite communications aka – the internet), used by disruptive enterprises (infinite insights – Hadoop style technologies), more widely used (infinite compute – from the cloud), the innovation layer (Infinite AI/ML – look at TensorFlow) and the frontier, almost not used yet (infinite deep learning). Adoption of the infinite compute technologies is key for enterprise survival.
• Next generation applications. As infinite computing becomes reality, technology capability overtakes best practice demands. Effectively, new best practices are being enabled and created. CxOs cannot afford to wait for their standard software vendors to provide these, as standard software vendors want to run the same software for hundreds if not thousands of customers. The result is that enterprises need to build software again and build their own next generation applications. The seven generic use cases for next generation applications are digitising value chains, tame the internet for demand chain usage, revolutionise intra-enterprise functions for the value chain and across the three chains to build IoT applications, enable data-as-a-service (DaaS), re-invent communication (Zoom anyone?) and innovate the human machine interface.
• Enterprise acceleration. Enterprises need to move faster and become more agile. To win they need to advance their people skills, improve their people processes, and provide modern platforms for their enterprise to excel. The speed of an enterprise needs to exceed the speed demands of the markets it wants to successfully compete in and the speed is determined by the potential and ability of its people as well as the technology platform. The inherent speed of the technology platforms dictates the limitation to enterprise velocity, therefore technology and software matter so much for enterprise success in the 21st century.
Handicapping the big three – and a dark horse
The cloud conversation has been dominated by the ‘big three’ – AWS, Azure and Google Cloud. While AWS and Microsoft battle for the number 1 spot in terms of market share, Google is a distant third. That forces Google to do things differently, to improve its value proposition and attraction to enterprises, while challenging the larger competitors and dictating the roadmap.
When understanding technology vendors it is always good to look at their organisational DNA:
• Amazon: Amazon is the prototypical showcase of a digital transformation winner, starting in the book business and then expanding into a lot of markets, and now one of the most valuable enterprises on the planet. Amazon is an electronic retailer; AWS is its IT platform. From its inception, AWS had to be elastic to cater for ecommerce peaks like Black Friday and other holidays. Amazon has key IP in supply chain management, logistics and warehousing automation, operating one of the most efficient fulfilment chains. Its AWS business is margin accreditive, meaning extra investment into AWS (compared to ecommerce) makes it more profitable. Lastly, Amazon has massive internal, organic load from its ecommerce business.
• Microsoft: Microsoft is a technology vendor in transformation mode, from its traditional Windows and Office franchise to Azure and more. Its CEO, Satya Nadella, came from the Azure business and is on a mission to turn Microsoft into a cloud company. Microsoft’s organisational DNA is that of a software company, not always the first and the best one, but the one that got it right for the enterprise and has multiple decades of relationships to technology decision makers around the world. Azure though remains margin dilutive for Microsoft, meaning Azure investment reduces Microsoft profitability (for now). Microsoft’s only substantial load is Office, and Office conversions to Office365 have been the bulk of the Azure load. Given the sensitive nature of Office data, Microsoft is at the forefront of data privacy and data residency requirements. • Google: Google had to ‘invent’ the cloud to scale for its mission – organising the world’s information and making it universally accessible and useful – by itself, a cloud scale challenge. Behind the scenes, Google lives from advertisement, with its eponymous search being the carrot to drive usage. As Google Cloud must scale to cloud scale problems (search, YouTube etc.) it has to be on the forefront of scale, TCO and speed. Google has a two-to-three year lead when it comes to AI, with its TensorBoard architecture entering their fourth revision. Quality, speed, and cost of AI will matter for enterprises more and more and Google banks on this to materialise. Google is also challenging the ‘only in my cloud’ approach with Anthos, operating across different cloud infrastructures, even building product with Big Query on that platform. It has successfully forced AWS and Azure to adopt and operate both Kubernetes and Tensorflow. Not bad for a number three with some distance. For Google, operating cloud is also margin dilutive, but it has massive organic load from search, voice (for all Android devices out there), YouTube and increasingly G Suite.
The dark horse: Oracle
Oracle has been a critical element of enterprises IT landscapes, pretty much from the start of the vendor in the 1970s. The Oracle organisational DNA is to build superior software products that win in the marketplace with functionality and total cost of ownership (TCO). Like many established vendors, Oracle has struggled moving to the cloud, only getting the equation right with Oracle Cloud Infrastructure Gen2. With its Exadata product line it is the best platform to run an Oracle Database, and with the full workload portability and identicality of its on-premise and cloud platforms, offers unique flexibility to enterprises. As long as Oracle remains a key database for enterprises, Oracle has a shot to become part of the current big three. For Oracle cloud is as well margin dilutive, when compared to its enterprise software business but margin accreditive when comparing to its hardware business. Oracle has substantial in-house load with its enterprise application portfolio, PaaS stack, and DaaS offerings.
It is key for CxOs to understand the different DNA and capabilities of the top three cloud vendors. They bring different value propositions to their customers. AWS will be the preferred platform by developers for the foreseeable future – and outside of the AI/ML space, where they are catching up – has done very well. Microsoft works well with IT and most enterprises use the vendor already. Google will be ideal for enterprises who want to bet on the AI/ML card today. In reality though, practically all enterprises operate in a multi-cloud world, using all cloud providers, and there is a high chance an enterprise with 5,000 employees is present on all three clouds. How to best operate them might be a good topic for a future piece in ERP Today. Watch this space.