McDermott sets the stage for Leonardo
During his keynote, aptly titled “Urgency of Doing,” SAP CEO Bill McDermott set the stage for Leonardo’s relevance to business today.
McDermott began by stressing that digital transformation is just beginning, is coming fast, and cannot be stopped. SAPPHIRE guest Michael Dell concurred, stating “the next 30 years will make the past 30 years look like child’s play.”
According to McDermott (and I agree), digital transformation is evidenced by the torrid pace with which companies are reinventing their business models, by “companies going from a world of making products to one of mass personalization as a service […] by companies evolving from commodity marketing to addressing an audience of one […] and by companies shifting from assets to networks in the sharing economy.”
Comparing today’s digital revolution to past technological revolutions (e.g., Industrial, Internet), McDermott astutely noted that there is no longer a buffer between early adopters and also-rans. “Only early adopters will win,” according to McDermott.
By way of underscoring the high stakes of digital transformation, McDermott cited a few scary stats of today’s digital disruption:
- ½ of Fortune 500 companies lost money in 2016
- Every two weeks a company falls out of the S&P 500
Leonardo is more of a toolbox or framework than a fully baked product or business application. It is comprised of accelerators and services designed to help customers connect the emerging world of intelligent devices with people and processes to achieve tangible business outcomes. Built on the SAP Cloud Platform, Leonardo combines Internet of Things (IoT), machine learning (ML), blockchain, Big Data in a comprehensive digital innovation system that, according to SAP, will enable customers to innovate at scale and redefine their business.
To help SAP customers wrap their minds around Leonardo and begin imagining how it can positively impact their business, it is helpful to first get an understanding of Leonardo’s cutting-edge constituent parts.
The Internet of Things (IoT)—a network of physical objects accessed through the Internet—has big implications for business. According to McKinsey, IoT applications could have an $11 trillion impact on the global economy by 2025. As reported in Forbes, analysts across the board are bullish on the rapidly emerging IoT category. Here’s a small selection of big IoT predictions:
- Worldwide spending on IoT will grow at a 17% compound annual growth rate (CAGR) from $698.6 billion in 2015 to nearly $1.3 trillion in 2019.
- By 2018, there will be 22 billion IoT devices installed, driving the development of over 200,000 new IoT apps and services.
- IoT will create between nearly $4 trillion to $11 trillion in economic benefits globally in the year 2025.
By itself, raw data from sensors and IoT devices has limited value. However, for organizations that successfully acquire, analyze and act on the data produced by myriad devices and their connections, IoT represents a transformational opportunity.
For example, predictive analytics applied to data streams from sensors and other IoT devices is driving a tectonic shift in maintenance practices from reactive to proactive, which helps companies in asset-intensive industries increase productivity, reduce downtime and maintenance costs, and ensure customer satisfaction.
The potential of IoT is virtually limitless and use cases span B2C and B2B worlds. Smart homes, offices and cities, security and surveillance, wearables, inventory and warehouse management, connected cars, utilities… the list is as endless as connected things can be imagined.
In a breakthrough driven by gaming, large-scale use of Graphic Processing Units (GPUs) quickly gave rise to deep learning algorithms. Together with quantum leaps in computing power, multi-core architectures, in-memory databases, and of course, big data (growing exponentially via IoT), extremely efficient implementations of machine learning (ML) algorithms are rapidly becoming the newest new thing in enterprise applications.
As reported in Forbes, one leading analyst firm predicts spending on machine learning will reach a staggering $47 billion by 2020.
At bottom, ML is the science of getting computers to act without being explicitly programmed. This is accomplished by applying ML algorithms and models to massive oceans of data in an iterative process. As models are exposed to new data, they are able to spot patterns and hidden trends, make connections, independently adapt, learn from previous computations and produce reliable, repeatable decisions and results.
Examples of Machine Learning abound in today's customer-centric world -- from recommendation engines built into Amazon and Netflix services, to face recognition capabilities of Facebook, to personal digital assistants in smartphones ... The list goes on ...
ML helps businesses automate highly repetitive, error-prone, time-consuming tasks, make fast, strategic decisions, and turn data into actions that advance business. Fraud detection, marketing personalization, HR recruiting, and payment processing are just the tip of the ML iceberg.
Check out these expert predictions and insights into Machine Learning's impact on business:
- Tractica forecasts the market for AI systems for enterprise applications will increase from $202.5 million in 2015 to $11.1 billion by 2024, expanding at a compound annual growth rate of 56.1%.
- As reported in WSJ, IDC predicts the worldwide market for cognitive software platforms and applications to grow to $16.5 billion in 2019 from $1.6 billion in 2015 with a CAGR of 65.2%.
- According to a recent MIT Sloan Management Review article, a survey of enterprises with at least $500M in sales that are targeting higher sales growth with machine learning found that 76% say they are targeting higher sales growth with machine learning; at least 40% of companies surveyed are already using machine learning to improve sales and marketing performance; and 38% credited machine learning for improvements in sales performance metrics.
Sometimes referred to as distributed ledger technology (DLT), blockchain is effectively a digital modern version of a traditional ledger run by a bank or accountancy. In its simplest form, blockchain is a reliable record of who owns what, and who transacts what. In a blockchain system, data regarding transactions, files, or information is shared across a peer-to-peer network. Every participant can see the data and verify or reject it using consensus algorithms. Approved data is entered into the ledger as a collection of 'blocks', stored in a chronological 'chain', which is secured through cryptography.
Blockchain is relevant to way more than financial companies. Specifically, companies who recognize that mastery of their supply chain leads to sustainable competitive advantages will increasingly stand to benefit in the understanding and application of blockchain technology, be it through superior tracking of assets, reduction in errors and elimination of fraud and theft.
A recent World Economic Forum report predicts that by 2025 10% of GDP will be stored on blockchains or blockchain related technology. According to many industry experts, the market for blockchain technology is poised to explode:
- According to MarketsandMarkets, the Blockchain market size is estimated to grow from $210.2 Million in 2016 to $2,312.5 Million by 2021, at a CAGR of 61.5% and will be in use by up to 65% of enterprise by 2020.
- According to Allied Market Research, The global Blockchain distributed ledger market accounted for $228 million in 2016, and between 2017 and 2023 is expected to reach $5.43 billion, expanding at a CAGR of 57.6%.
Compared to the term ‘big data,’ IoT, ML and blockchain are relative newcomers to the business lexicon. As buzzwords bouncing around boardrooms, these terms have little value other than completing your buzzword bingo card. But when put in the context of big data – something every business has in abundance, these terms rightly shine forth as the gold they represent. In many respects, IoT, ML and blockchain are the offspring of big data, the fruit of quantum leaps in processing power, affordable storage, and the explosion of big data in your enterprise.
Not too long ago, circa 2000, organizations and executives were struggling to understand the opportunity and business impact of big data. Fast forward to today, and analytics on big data has become a corporate standard, with an increasing focus on the results it produces, the business capabilities it enables, and the opportunities — IoT, ML, blockchain — it fosters.
According to a recent study reported in Harvard Business Review, big data is getting the attention it deserves in the corporate world:
- 63% of firms now report having big data in production in 2015, up from just 5% in 2012
- 63% of firms reported that they expect to invest greater than $10 million in big data by 2017, up from 24% in 2012
- 54% of firms say they have appointed a Chief Data Officer, up from 12% in 2012
- 70% of firms report that big data is of critical importance to their firms, up from 21% in 2012
- At the top end of the investment scale, 27% of firms say they will invest greater than $50 million in big data by 2017, up from 5% of firms that invested this amount in 2015
Expert guidance needed
It is no exaggeration to say that in business today survival hinges on embedding IoT, ML, blockchain, big data as well as other digital technologies into enterprise applications. To this end, Leonardo goes a long way.
But for Leonardo to deliver real-word business value, SAP and SAP partners such as NTT DATA must work with businesses to identify opportunities to apply these next-gen technologies (in the correct combination) and design winning business models that effectively leverage new-found ‘systems of intelligence.’
At NTT DATA, we applaud SAP for bringing together these cutting-edge digital technologies in an offering that underscores their interrelatedness and the need of an action plan to realize their value. While we look forward to putting the technological aspects of Leonardo through their paces in our SAP Solution centers, the truth is NTT DATA is no stranger to these digital technologies and has been helping our customers discover and implement real-world applications based on these (and other) digital technologies for many years.
The pace of digital transformation is faster than ever, the scope broader, and the urgency driving digital initiatives is at an all-time high. More than ever before, the pressure is on SAP and SAP partners to not only identify digital opportunities for customers but to also provide a prioritization framework, best practices, and the infrastructure-to-application capabilities needed to guide a holistic, pragmatic and sustainable transformation strategy.
Contact NTT DATA today to learn how we can we can help your business stay ahead of the digital curve.