The Agile Manifesto
Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.
Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage.
Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.
Business people and developers must work together daily throughout the project.
Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.
The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.
Working software is the primary measure of progress.
Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.
Continuous attention to technical excellence and good design enhances agility.
Simplicity–the art of maximizing the amount of work not done–is essential.
The best architectures, requirements, and designs emerge from self-organizing teams.
At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.
Embrace new technology, adapt business models to succeed in the market, and be intently focused on the customer to drive the best outcomes are a few essential rules the marketing teams must follow. Creating the best experience, whether it is for partners or customers, is still the key. Marketers constantly energized by new ideas, and ability to execute in creative ways with a data-driven approach is the differentiator.
The agile approach is still new for most tenured CMOs. Many have built successful careers using methods that mirror and reward a prioritization of hard skills. Although these skills are still imperative, they must be balanced and flexed with soft skills. Hard skills are often easier to teach than soft skills, which develop over a longer period of time and can align with natural aptitudes.
Marketing organizations have a very strategic role to play for the business, and this is increasingly becoming critical. Key practices that need to be embraced may be defined as:
- Businesses will need to adapt their marketing organizations to be agile, and this can only happen if they are fueled by data;
- Using market and customer insights is critical to agile marketing; and
- Marketers must also be creative and resourceful to succeed in an agile marketing organization.
Enterprises are adopting new IT-delivery models and applications that require fundamental network changes from device access to the network core. To improve the agility and rate of innovation of their networks, the marketing teams must have in place I&O teams and provide the backup to drive mindset changes toward agile processes and versatile people.
The marketing landscape never stays the same for very long. As 2019 progresses, B2B marketers are seeing old trends evolve and new strategies emerge. Disruptions like machine learning and artificial intelligence are changing the way B2B buyers interact with brands online. With so many tools to choose from, picking the perfect strategy is a difficult challenge. In fact, choosing just one strategy is not enough anymore. Businesses must have the ability to stay agile and choose a mix of tools and strategies that improve the buying experience.
As organizations across industries continue to expand their ongoing digital transformation efforts, it is imperative that the marketing teams stay ahead.
AI is coming to enterprise networks in a number of ways, but the most fundamental shift will likely be on hardware. As can be expected, AI workloads are quite large and quite complicated, incorporating sophisticated algorithms, abundant compute cycles, and highly dynamic data management. Already, leading organizations are finding it difficult to handle all of this on traditional CPUs, GPUs, and FPGAs, which is why the processor industry is working overtime to produce new generations of AI-ready silicon.
According to Allied Market Research, the AI chip sector is on pace to top USD 91 billion by 2025, a more than ten-fold increase from today’s already hefty USD 4.5 billion valuation. The technology has seen a steady flow of capital investment over the past year, as talk of smart cities and smart homes has ramped up and research has shown the increasing viability of quantum computing. On the downside, however, management and utilization of smart chips is vastly different from current technology, which is likely to produce a dearth of skilled workers in the coming years. While AI-driven networking will certainly find a home in the data center, the real action will likely take place on the IoT edge, where all manner of traffic patterns and data use cases will emerge. Much of this edge infrastructure will be unmanned, of course, so the enterprise will be in desperate need of technology that can make decisions regarding the optimal means to achieve the desired results.
The whole world is getting smarter, and it has reached its current stage primarily through advances in networking. It only stands to reason that the network itself will become smarter as well, right down to its hardware roots.
While the IoT is already churning out massive volumes of data, this is only a slight fraction of what is likely to arise over the next decade. Virtually everything that we see and touch, and perhaps even parts of our own bodies, will soon be generating continuous data streams to processing and storage elements on the edge and in centralized data facilities, where it will be parsed, analyzed, combined, and otherwise manipulated – theoretically to the benefit of the connected public.
Gartner predicts the eventual transition from an intelligent edge to an intelligent mesh. This architecture will be much more flexible and responsive to IoT workloads and systems even as it becomes more complex. In this way, the IoT will foster greater connectivity between edge resources and even between endpoint devices themselves, essentially replacing today’s point-to-point solutions with a new layer of multipoint-to-multipoint fabrics.
The IoT will undoubtedly see continuous development across a wide range of functions, such as security, governance, and the like, but the focus for the coming year will be to push today’s largely behind-the-scenes operations to the forefront of the digital economy. Once it becomes a service- and revenue-generator in its own right, rather than a mere extension of legacy infrastructure, we will safely be able to say that we live in a truly connected universe.
For AI and IoT, however, virtual networks cannot do it all
One of the ideas behind virtual networking is that it allows organizations to create highly specialized architectures that suit the unique needs of individual applications – all in software.
While this may work for many of today’s back-office and customer-facing workloads, the fact remains that many emerging technologies require highly specialized environments of their own, some of which require substantial changes to core infrastructure.
For the enterprise, perhaps the most difficult aspect of these changes is that they are being driven by application and user demands rather than advancements in technology. In the past, new networking capabilities were deployed, then the user community set to work exploiting them to the greatest extent (and then immediately calling for newer, better technology). This time, the use cases are being defined first, and the networking team is expected to fulfill them or watch users gravitate to another network.
Making this happen on a virtual network is problematic enough; overhauling bare-metal infrastructure and basic communications protocols is going to take some time. And time is in increasingly short supply as the digital economy moves forward.
Network-as-a-service (NaaS) is poised to make dramatic inroads into enterprise infrastructure, and why not? Once the network is defined as a virtual architecture, there is no reason to continue managing it as a piece of fixed infrastructure.
But just like there are differences in service-based compute, storage, and applications, there are differences in NaaS that can make or break any given digital initiative.
Like all as-a-service offerings, the real benefit of NaaS is that it replaces a fixed cost with a more flexible, consumption-based model that lets you pay only for what you use. This will become increasingly important as enterprise infrastructure expands into the cloud and all the way to the IoT edge, connecting all manner of endpoints on wired, wireless, virtual, and physical infrastructure.
The need for fixed connectivity will not recede, of course, and in fact, it might actually expand. But a network defined as service will provide optimal support for everything else that is currently experiencing a service transition, which in the end will likely enhance all forms of traditional infrastructure.
Robotics process automation
Probably the most interesting aspect of the current drive to automate the enterprise is robotics process automation (RPA). Although the name invokes walking, talking automatons milling about the office, the reality is a bit more nuanced.
In this case, robotics refers to software bots that constitute a virtual workforce to take on many of the rote, mundane tasks that highly paid knowledge professionals currently spend the majority of their time doing. With RPA, the idea is not to displace these workers but to free up their time to more productive pursuits, such as tapping new markets and creating new revenue streams.
Under a rules-based system, RPA applies decisions according to specific rules laid down by the operator. This gives the enterprise a good deal of assurance that the system will behave as expected – a crucial requirement when it comes to managing IT resources, streamlining supply chains and making payroll. But this does not mean knowledge-based systems have no value. In fact, we can expect to see knowledge automation take the lead in analytics and cognitive processes where the end result is to make recommendations rather than take specific actions.
One thing that could undermine the whole RPA movement, however, is lack of uniformity. Many of these bots will have to navigate far outside the confines of an individual enterprise’s infrastructure to engage with IoT, regional networking infrastructure, and other enterprises.
Expectations are that RPA will take the enterprise by storm in the next few years, but this will only happen once the executive suite is convinced they will be a help, not a hindrance, to the broader goal of digital transformation. At this point, there is every reason to think their impact will be positive, provided those who are developing this technology place their customers’ interests above their own.
Security needs to automate too. Perhaps the most important reason security needs to jump on the automation bandwagon is because hackers and other wrongdoers are most certainly heading in this direction as well. With intelligent automation platforms and codes readily available on the internet, along with the hyperscale cloud resources to use them, the bad guys have all the tools they need to make life miserable for organizations that fail to effectively automate their security postures. Like all other elements in the IT stack, security has to keep up with the times.
“I think that what we are beginning to see…is that while the cloud four or five years ago was viewed as an existential threat to our business, I fundamentally believe that the cloud and the transition to the cloud that our customers are undergoing is actually driving our growth now,” said Chuck Robbins, CEO, Cisco at the company’s Q1 financial teleconference in November 2018. And that perhaps sums it all.
The insights that we formulate on various aspects and developments in the network is what leads to strategic decision-making – fueled by the insights of an agile and creative marketing organization. It is clear, marketing has a strategic seat at the table with business leaders. Get creative and connect in meaningful ways. And fuel everything with insights. And that in a nutshell is agile marketing!