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Shifting Priorities in the Age of Digital Transformation & The Evolving 5G Technology
Creating the analytics-driven enterprise with a “strategic enterprise intelligence system”
In the Age of Digital Transformation, executives concerned with creating competitive advantage are laser-focused on the vitally important question:
“How can I use technology to beat the competition and avoid disruption?”
This deceptively simple question tends to open a can of worms when we attempt to answer it. On a daily basis, executives seek to simplify complex answers by deconstructing them into their component parts. By doing so, they hope to define and deploy said components on an operational level to create a better, stronger operating -model.
This is the very foundation of the analytics-driven enterprise.
We hope to help executives deconstruct the complex questions they face regarding their investments in the technologies needed to secure a competitive advantage in the 21st century.
Enlightened executives have shifted their priorities to compete in the digital age. To be a digital competitor today, the CEO and their team must leverage technology to:
· Drive revenue productivity – drive increasing rates of revenue with continuously lower variable operating costs by accelerating marginal revenues faster than marginal costs. Wall Street rewards public companies for their organic revenue growth more than any other KPI.
· Improve operational efficiencies – automate where automation makes sense, and drive continuous streamlining and improvement of key business processes that provide value at an increasingly lower cost.
· Enhance the customer experience – create a brand experience that insulates the customer base from competitive attacks and mitigates the risk of being disrupted by either traditional competitors or new entrants.
· Monetize data assets – gather, store, analyze, and move digitally-derived insights to where they are needed to drive operations, service, sales and marketing. Leveraging the company’s own unique data assets is the key to “cracking the code” and winning in the 21st
Enlightened executives have come to understand that next to their people, data is their most valuable corporate asset. The ability to leverage 21st century technologies to monetize data has resulted in an explosion of technologies of many different types designed to generate high ROI and sustainable competitive advantage from data assets residing both inside and outside of the enterprise.
Data analytics and Business Intelligence (BI) technologies are included in those high-ROI technologies. As evidence of the digital transformation explosion currently underway, in September of 2020 the cloud data warehousing firm Snowflake recorded the largest initial public offering in history. The company sold 28 million shares to raise nearly $3.4 billion. After trading over $300, Snowflake stock closed at $253.93, up 112% from its offering price. Warren Buffet’s Berkshire Hathaway fund is a major investor.
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Cloud is but one component. The digital transformation market based on technology is segmented into cloud computing, AI, big data and analytics, mobility/social media, cyber security, IoT, and others. The global digital transformation market size is projected to grow at a CAGR of 16.5% from USD 469.8 billion in 2020 to USD 1009.8 billion by 2025. The AI segment is expected to grow at 30% + CAGR during the same period.
The emergence of big data as a source of competitive advantage has changed everything. The hype rages on as the continuous, 24/7/365 onslaught of structured and unstructured data has triggered both unprecedented opportunities and major disappointment.
Cutting through the hype surrounding big data and making it actionable has been a major source of heartburn for business teams. As a result, the technologies associated with making big data actionable—organizing it, analyzing it, and creat
ing useable output that drives the four priorities outlined above—has become a priority for global enterprises across all sectors.
Managing and monetizing this “Big Data Tsunami” has become a top priority for CEOs around the globe.
The Rise of Business Intelligence (BI) Tools
Business Intelligence tools include key features such as data visualization, visual analytics, interactive dash-boarding, and KPI scorecards with minimal IT support. They allow business users to utilize automated reporting and predictive analytics in a self-service mode to operate the business and build their “strategic enterprise intelligence system.”
Becoming an analytics-driven enterprise is essential in the Age of Digital Transformation, where start-ups are emerging in every sector, taking share from established brands, and inhibiting improvement in core KPIs.
The data analytics BI tools served up in visualization dashboards typically consist of four categories: 1) Diagnostic, 2) Descriptive, 3) Predictive, and 4) Prescriptive. Diagnostic and Descriptive analytics tell the company what happened and why, while Predictive and Prescriptive analytics tell the company what to do and when to do it.
Properly integrated, a strategic BI solution can let the business both look “in the rearview mirror” (diagnostic and descriptive reporting) and “through the windshield into the future” (predictive and prescriptive actions). This allows the company to optimize its approach to customers, products, and markets, as well as drive core KPIs to new levels.
BI tools, when integrated properly with other data and analytics assets and organized for the unique needs of the business, can create a strategic enterprise intelligence system. Their benefits include:
1. Data consolidation across business unit, data and technology silos—a single version of the truth at the enterprise level
2. Self-service analytics unlock data access so data can be monetized
3. Elimination of manual tasks
4. Reduced costs
5. Real-time access and reporting
Today, the world’s most innovative companies are using complex combinations of these commercially available suites combined with their own proprietary data analytics to drive the performance of these suites to even higher levels.
Network slicing: The defining characteristics of 5G Technology
The reality is something in between, but while there may be some over-hype on the side of 5G supporters, it would simply be wrong to label 5G as “LTE on steroids”. There are some things 5G does that 4G simply cannot do. One of the most crucial is network slicing –the gateway to some exciting opportunities.
Custom network configuration -- known as network slicing -- is one of the most unique characteristics of 5G. In fact, it may be thought of as the most significant difference between 4G and 5G. In previous generations of wireless, the networks were configured universally, and each customer, each network operator had few options for customisation or optimisation of their network configuration. As the technology has evolved, certain aspects of it are more well-suited to certain types of vertical applications, each requiring different levels of performance. Put simply, network slicing allows operators to offer customised resources for the different types of applications running on their network.
A recent research paper published by Heavy Reading entitled ‘5G Deployment & Service Strategies’ found that network operators are generally optimistic about the value of network slicing. In fact, more than 70 per cent of network operators report plans to deploy network slicing to some degree within three years of commercial launch of their 5G service.
What will it look like?
It's important to think about network slicing as a truly end-to-end concept. It applies to the entire network: from the user equipment, to the radio network, to the core network, and beyond that to the transport network, the cloud and application servers. Yet, it's the 5G core network that makes network slicing possible, which would have otherwise been impossible with LTE.
There are tremendous efficiencies to be gained with network slicing, both on the side of the network operator and on the side of the end-user. If we look at the differences between an autonomous vehicle application, a healthcare application, or a massive IoT application, all require different types of resources. Some are very resource intensive or bandwidth intensive, while some require high levels of resilience, and others require a certain level of quality of service (QoS) or quality of experience (QoE). For each of these different use cases, the network operator will be able to use network slicing to customise the network and in effect, make it as efficient as possible.
For instance, a healthcare provider might require some very high reliability and low latency type of resources in their networked applications, and some redundancies when applications like remote surgery or heart monitoring run on the network. The healthcare provider needs very high reliability on these
applications because the consequences of low reliability can be devastating. For this type of network slice, the operator will make sure there's enough redundant resources on the network to ensure this ultra-high level of reliability.
In the case of an IoT application, the needs are different. The main type of IoT data flowing over the network will be small data from things like sensors. In that case, reliability isn't nearly as much of a factor as management of a very high number of connections. So those particular resources can be sliced differently for this use case. In addition to this, things like mobility management might not be particularly important for a large IoT network, because many of the connected devices might not move around very much, if at all. Without the need to provision mobility for a network of millions of devices, the operator can save on capital expenditure, and savings on a significant amount of network resources can be realised as well. This kind of network would be sliced to optimise for a high volume of connections, rather than the highly redundant, low latency, high bandwidth network slice we imagined in the healthcare scenario.
These different scenarios (along with the many others, all with their own specific requirements) all provide significant benefit to the operators in particular, who can now offer more customised (and appropriately priced) solutions to their customers, as opposed to the older models where an operator had to try their best to offer a one-size-fits-all solution. With this type of virtualised architecture, customers will be able to finally deploy networked solutions that are tailored to fit their specific needs.
Networking slicing and 5G
The Heavy Reading research paper also indicated that, while overall sentiment is positive about network slicing, roughly 30 per cent of operators indicated they'd be making limited or no use of slicing in the early years of 5G commercialization. This is likely because in the early years of 5G, the majority of use cases will be focused around providing enhanced mobile broadband (eMBB), which will look more like an extension of what we already see today with LTE use cases. In fact, the early 5G mobile broadband use cases may not require much network slicing at all.
But as time goes by, as 5G infrastructure is built out, and as we move closer to fully standalone 5G, more slices will emerge. These will be enabled by 5G core network deployments to cater to the many different use cases that 5G will open up the doors too.
Quite simply: 5G-enabled network slicing will enable far more applications and use cases than we can possibly think up. The capabilities of network slicing will make possible new scenarios: for example, autonomous vehicles, and IoT services.
These types of network configurations and these many different types of connections even aren’t possible with 4G, and it will be interesting to see how these scenarios and many others evolve in the coming years.
5G connections set to soar by 2025
The number of 5G connections is set to soar within half a decade, according to a new report from market analysts CCS insight.
The new report, which analyzes the state of the 5G infrastructure, claims the world will have almost a quarter of a billion 5G connections by the end of this year, with that figure set to triple in 2021.
Perhaps surprisingly, it’s not the industrial usage that is going to propel 5G in the years to come, but rather consumer usage. That means smart phones, but also internet-connected laptops, tablets and other consumer-oriented internet-connected technologies.
China will be the number one driver, with 5G adoption “defying previous expectations,” the report said. More than half of new smart phones sold in the past three months support 5G, mostly due to strong promotion from three of the country’s main mobile operators.
By the end of the year, the analysts expect more than 170 million 5G-enabled
phones in China alone. Globally, 260 million units are expected to be sold this year, jumping to 630 million next year.
Based on the proportion of connections, South Korea is still the number one market, with a 12 percent penetration this August. About a third of all mobile data traffic in the country is now on 5G.
"Ironically, the weak overall demand for smartphones worldwide has been one of the triggers for 5G's success", observed Marina Koytcheva, VP of Forecasting at CCS Insight.