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Posts from the ‘CIO’ Category

10 Ways AI & Machine Learning Are Revolutionizing Omnichannel

Disney, Oasis, REI, Starbucks, Virgin Atlantic, and others excel at delivering omnichannel experiences using AI and machine learning to fine-tune their selling and service strategies. Source: iStock

Bottom Line: AI and machine learning are enabling omnichannel strategies to scale by providing insights into the changing needs and preferences of customers, creating customer journeys that scale, delivering consistent experiences.

For any omnichannel strategy to succeed, each customer touchpoint needs to be orchestrated as part of an overarching customer journey. That’s the only way to reduce and eventually eliminate customers’ perceptions of using one channel versus another. What makes omnichannel so challenging to excel at is the need to scale a variety of customer journeys in real-time as customers are also changing.

89% of customers used at least one digital channel to interact with their favorite brands and just 13% found the digital-physical experiences well aligned according to Accenture’s omnichannel study. AI and machine learning are being used to close these gaps with greater intelligence and knowledge. Omnichannel strategists are fine-tuning customer personas, measuring how customer journeys change over time, and more precisely define service strategies using AI and machine learning. Disney, Oasis, REI, Starbucks, Virgin Atlantic, and others excel at delivering omnichannel experiences using AI and machine learning for example.

Omnichannel leaders including Amazon use AI and machine learning to anticipate which customer personas prefer to speak with a live agent versus using self-service for example. McKinsey also found omnichannel customer care expectations fall into the three categories of speed and flexibility, reliability and transparency, and interaction and care. Omnichannel customer journeys designed deliver on each of these three categories excel and scale between automated systems and live agents as the following example from the McKinsey article, How to capture what the customer wants illustrate:

The foundation all great omnichannel strategies are based on precise customer personas, insight into how they are changing, and how supply chains and IT need to flex and change too. AI and machine learning are revolutionizing omnichannel on these three core dimensions with greater insight and contextual intelligence than ever before.

10 Ways AI & Machine Learning Are Revolutionizing Omnichannel

The following are 10 ways AI & machine learning are revolutionizing omnichannel strategies starting with customer personas, their expectations, and how customer care, IT infrastructure and supply chains need to stay responsive to grow.

  1. AI and machine learning are enabling brands, retailers and manufacturers to more precisely define customer personas, their buying preferences, and journeys. Leading omnichannel retailers are successfully using AI and machine learning today to personalize customer experiences to the persona level. They’re combining brand, event and product preferences, location data, content viewed, transaction histories and most of all, channel and communication preferences to create precise personas of each of their key customer segments.
  2. Achieving price optimization by persona is now possible using AI and machine learning, factoring in brand and channel preferences, previous purchase history, and price sensitivity. Brands, retailers, and manufacturers are saying that cloud-based price optimization and management apps are easier to use and more powerful based on rapid advances in AI and machine learning algorithms than ever before. The combination of easier to use, more powerful apps and the need to better manage and optimize omnichannel pricing is fueling rapid innovation in this area. The following example is from Microsoft Azure’s Interactive Pricing Analytics Pre-Configured Solution (PCS). Source: Azure Cortana Interactive Pricing Analytics Pre-Configured Solution.

  1. Capitalizing on insights gained from AI and machine learning, omnichannel leaders are redesigning IT infrastructure and integration so they can scale customer experiences. Succeeding with omnichannel takes an IT infrastructure capable of flexing quickly in response to change in customers’ preferences while providing scale to grow. Every area of a brand, retailer or manufacturer’s supply chain from their supplier onboarding, quality management and strategic sourcing to yard management, dock scheduling, manufacturing, and fulfillment need to be orchestrated around customers. Leaders include C3 Solutions who offers a web-based Yard Management System (YMS) and Dock Scheduling System that can integrate with ERP, Supply Chain Management (SCM), Warehouse Management Systems (WMS) and many others via APIs. The following graphic illustrates how omnichannel leaders orchestrate IT infrastructure to achieve greater growth. Source: Cognizant, The 2020 Customer Experience.

  1. Omnichannel leaders are relying on AI and machine learning to digitize their supply chains, enabling on-time performance, fueling faster revenue growth. For any omnichannel strategy to succeed, supply chains need to be designed to excel at time-to-market and time-to-customer performance at scale. 54% of retailers pursuing omnichannel strategies say that their main goal in digitizing their supply chains was to deliver greater customer experiences. 45% say faster speed to market is their primary goal in digitizing their supply chain by adding in AI and machine learning-driven intelligence. Source: Digitize Today To Future-Proof Tomorrow (PDF, 16 pp., opt-in).

  1. AI and machine learning algorithms are making it possible to create propensity models by persona, and they are invaluable for predicting which customers will act on a bundling or pricing offer. By definition propensity models rely on predictive analytics including machine learning to predict the probability a given customer will act on a bundling or pricing offer, e-mail campaign or other call-to-action leading to a purchase, upsell or cross-sell. Propensity models have proven to be very effective at increasing customer retention and reducing churn. Every business excelling at omnichannel today rely on propensity models to better predict how customers’ preferences and past behavior will lead to future purchases. The following is a dashboard that shows how propensity models work. Source: customer propensities dashboard is from TIBCO.

  1. Combining machine learning-based pattern matching with a product-based recommendation engine is leading to the development of mobile-based apps where shoppers can virtually try on garments they’re interested in buying. Machine learning excels at pattern recognition, and AI is well-suited for creating recommendation engines, which are together leading to a new generation of shopping apps where customers can virtually try on any garment. The app learns what shoppers most prefer and also evaluates image quality in real-time, and then recommends either purchase online or in a store. Source: Capgemini, Building The Retail Superstar: How unleashing AI across functions offers a multi-billion dollar opportunity.

  1. 56% of brands and retailers say that order track-and-traceability strengthened with AI and machine learning is essential to delivering excellent customer experiences. Order tracking across each channel combined with predictions of allocation and out-of-stock conditions using AI and machine learning is reducing operating risks today. AI-driven track-and-trace is invaluable in finding where there are process inefficiencies that slow down time-to-market and time-to-customer. Source: Digitize Today To Future-Proof Tomorrow (PDF, 16 pp., opt-in).
  2. Gartner predicts that by 2025, customer service organizations who embed AI in their customer engagement center platforms will increase operational efficiencies by 25%, revolutionizing customer care in the process. Customer service is often where omnichannel strategies fail due to lack of real-time contextual data and insight. There’s an abundance of use cases in customer service where AI and machine learning can improve overall omnichannel performance. Amazon has taken the lead on using AI and machine learning to decide when a given customer persona needs to speak with a live agent. Comparable strategies can also be created for improving Intelligent Agents, Virtual Personal Assistants, Chatbot and Natural Language (NLP) performance.  There’s also the opportunity to improve knowledge management, content discovery and improve field service routing and support.
  3. AI and machine learning are improving marketing and selling effectiveness by being able to track purchase decisions back to campaigns by channel and understand why specific personas purchased while others didn’t. Marketing is already analytically driven, and with the rapid advances in AI and machine learning, markets will for the first time be able to isolate why and where their omnichannel strategies are succeeding or failing. By using machine learning to qualify the further customer and prospect lists using relevant data from the web, predictive models including machine learning can better predict ideal customer profiles. Each omnichannel sales lead’s predictive score becomes a better predictor of potential new sales, helping sales prioritize time, sales efforts and selling strategies.
  4. Predictive content analytics powered by AI and machine learning are improving sales close rates by predicting which content will lead a customer to buy. Analyzing previous prospect and buyer behavior by persona using machine learning provides insights into which content needs to be personalized and presented when to get a sale. Predictive content analytics is proving to be very effective in B2B selling scenarios, and are scaling into consumer products as well
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Digital Transformation’s Missing Link Is Zero Trust

    • Enterprises will invest $2.4T by 2020 in digital transformation technologies including cloud platforms, cognitive systems, IoT, mobile, robotics, and integration services according to the World Economic Forum.
    • Digital transformation software and services revenue in the U.S. is predicted to reach $490B in 2025, soaring from $190B in 2019, attaining a Compound Annual Growth Rate (CAGR) of 14.49% according to Grand View Research published by Statista.
    • IDC predicts worldwide spending on the technologies and services that enable the digital transformation of business practices, products, and organizations will reach $1.97T in 2022.
    • Legacy approaches to Privileged Access Management (PAM) don’t protect the new threatscapes digital transformation initiatives create, making Zero Trust Privilege essential for enterprises.

B2B customers, including manufacturers looking to replace legacy production equipment with smart, connected machines, have high expectations when it comes to product quality, ease of integration, and intuitive user experiences. Replacing factories full of legacy assets with smart, connected machinery is one of the most powerful catalysts driving digital transformation today. Innovative smart, connected machinery and the performance gains they provide are the oxygen that keeps customer relationships alive. That’s why digital transformation forecasts from the World Economic Forum, Grand View ResearchIDC, and many others predict perennial growth. The many forecasts reflect a fundamental truth: digital transformation done with intensity creates a customer-driven renaissance for any business.

Businesses digitally transforming themselves are succeeding because they’ve made themselves accountable and transparent to customers. Earning and protecting that trust is the heartbeat of any business’ growth. 51% of enterprises invest in digital transformation to capture growth opportunities in new markets, with 46% investing to stay in front of evolving customer behaviors and preferences. Brian Solis’ excellent report, The State of Digital Transformation, 2018 – 2019 Edition (31 pp., PDF, opt-in) shows how digitally transforming any business with the customer first leads to greater growth. The graphic from his study illustrates this point:

 

Closing The Digital Transformation Gap With Zero Trust

Gaps exist between the results digital transformation initiatives are delivering today, and the customer-driven value they’re capable of. According to Gartner, 75% of digital transformation projects are not aligned internally today, leading to delayed new product launches, mediocre experiences, and greater security risks than ever before. Interactive, IoT-enabled experiences and products are expanding the threatscape of enterprises to include Big Data, cloud, containers, DevOps, IoT systems, and more. With that comes a host of new exposure points, many of which allow access to sensitive data that must be protected with modern Privileged Access Management solutions that reduce risk in these modern enterprise use cases.

The new security perimeter is identity. Forrester estimates that 80% of data breaches are caused by privileged access abuse. Every smart, connected machine that replaces legacy production equipment is another identity that defines a manufacturer’s security perimeter.

As the use cases and adoption of smart, connected machines proliferate, so too does the urgency that manufacturers need to replace their legacy approaches to Privileged Access Management (PAM). Relying on outdated strategies for protecting administrative access to all machines needs to be replaced with a “never trust, always verify, enforce least privilege” approach.

IT needs to improve how they’re protecting the most privileged access credentials, the ‘keys to the kingdom,’ by granting just-enough, just-in-time privilege. Of the many cybersecurity approaches available today, Zero Trust Privilege (ZTP) enables IT to grant least privilege access based on verifying who is requesting access, the context of the request, and the risk of the access environment.

The more diverse any digital transformation strategy, the greater the risk of privileged credential abuse. Thwarting privileged credential abuse needs to start with a least privilege access approach, minimizing each attack surface, improving audit and compliance visibility while reducing risk, complexity, and costs. Leaders in Zero Trust include CentrifyMobileIronPalo Alto Networks, and others. Of these companies, Centrify’s approach to Zero Trust to prevent privileged access abuse shows the greatest potential for securing digital transformation initiatives and strategies.

How To Secure Digital Transformation Strategies

IDG Research found in their Security Priorities for 2018 study that 71% of security-focused IT decision-makers are aware of the Zero Trust model and 18% of enterprises are either running pilots or have implemented Zero Trust.

Zero Trust Privilege (ZTP) is the force multiplier digital transformation initiatives need to reach their true potential by securing administrative access to the complex mix of machinery and infrastructure – and the sensitive data they hold and use – that manufacturers rely on daily.

Starting with a strategic perspective, ZTP’s contribution to securing digital transformation deployments apply to every area of planning, pilots, platforms, product, and service data being designed to stop the leading cause of breaches, which is privileged credential abuse. The following graphic illustrates how ZTP needs to span every aspect of an enterprise’s digital transformation capabilities.

Source: World Economic Forum, Digital Transformation Initiative, May 2018

Conclusion

By 2020, 30% of Global 2000 companies will have allocated capital budget equal to at least 10% of revenue to fuel their digital transformation strategies according to IDC.  European spending on technologies and services that enable the digital transformation of business practices, products, and organizations is forecasted to reach $378.2B in 2022. The perennial growth these forecasts promise is predicated on enterprises delivering new experiences and innovative products, which create the oxygen that keeps their customer relationships alive.

Amidst all the potential for growth, enterprises need to realize every new infrastructure element, machine, or connected production asset is a new identity that collectively comprises the fabric of their security perimeter. Legacy cybersecurity approaches won’t scale to protect the proliferating number of smart machines being put into use today. Relying entirely on legacy approaches to PAM, where privileged access to systems and resources only inside the network are secure, is failing today. Smart, connected machinery and the products and experiences they deliver require an entirely new cybersecurity strategy, one based on a “never trust, always verify, enforce least privilege” approach. Centrify Zero Trust Privilege shows potential to meet this challenge by granting least privilege access based on verifying who is requesting access, the context of the request, and the risk of the access environment.

86% Of Enterprises Increasing IoT Spending In 2019

  • Enterprises increased their investments in IoT by 4% in 2018 over 2017, spending an average of $4.6M this year.
  • 38% of enterprises have company-wide IoT deployments in production today.
  • 84% of enterprises expect to complete their IoT implementations within two years.
  • 82% of enterprises share information from their IoT solutions with employees more than once a day; 67% are sharing data in real-time or near real-time.

These and many other fascinating insights are from Zebra Technologies’ second annual Intelligent Enterprise Index (PDF, 25 pp., no opt-in). The index is based on the list of criteria created during the 2016 Strategic Innovation Symposium: The Intelligent Enterprise hosted by the Technology and Entrepreneurship Center at Harvard (TECH) in 2016. An Intelligent Enterprise is one that leverages ties between the physical and digital worlds to enhance visibility and mobilize actionable insights that create better customer experiences, drive operational efficiencies or enable new business models, “ according to Tom Bianculli, Vice President, Technology, Zebra Technologies.

The metrics comprising the index are designed to interpret where companies are on their journeys to becoming Intelligent Enterprises. The following are the 11 metrics that are combined to create the Index: IoT Vision, Business Engagement, Technology Solution Partner, Adoption Plan, Change Management Plan, Point of use Application, Security & Standards, Lifetime Plan, Architecture/Infrastructure, Data Plan and Intelligent Analysis. An online survey of 918 IT decision makers from global enterprises competing in healthcare, manufacturing, retail and transportation and logistics industries was completed in August 2018. IT decision makers from nine countries were interviewed, including the U.S., U.K./Great Britain, France, Germany, Mexico, Brazil, China, India, and Australia/New Zealand. Please see pages 24 and 25 for additional details regarding the methodology.

Key insights gained from the Intelligent Enterprise Index include the following:

  • 86% of enterprises expect to increase their spending on IoT in 2019 and beyond. Enterprises increased their investments in IoT by 4% in 2018 over 2017, spending an average of $4.6M this year. Nearly half of enterprises globally (49%) interviewed are aggressively pursuing IoT investments with the goal of digitally transforming their business models this decade. 38% of enterprises have company-wide IoT deployments today, and 55% have an IoT vision and are currently executing their IoT plans.

  • 49% of enterprises are on the path to becoming an Intelligent Enterprise, scoring between 50 – 75 points on the index. The percent of enterprises scoring 75 or higher on the Intelligent Enterprise Index gained the greatest of all categories in the last 12 months, increasing from 5% to 11% of all respondents. The majority of enterprises are improving how well they scale the integration of their physical and digital worlds to enhance visibility and mobilize actionable insights. The more real-time the integration unifying the physical and digital worlds of their business models, the better the customer experiences and operational efficiencies attained.

  • The majority of enterprises (82%) share information from their IoT solutions with employees more than once a day, and 67% are sharing data in real-time or near real-time. 43% of enterprises say information from their IoT solutions is shared with employees in real-time, up 38% from last year’s index. 76% of survey respondents are from retailing, manufacturing, and transportation & logistics. Gaining greater accuracy of reporting across supplier networks, improving product quality visibility and more real-time data from distribution channels are the growth catalysts companies competing in retail, manufacturing, and transportation & logistics need to grow. These findings reflect how enterprises are using real-time data monitoring to drive quicker, more accurate decisions and be more discerning in which strategies they choose. Please click on the graphic to expand to view specifics.

  • Enterprises continue to place a high priority on IoT network security and standards with real-time monitoring becoming the norm. 58% of enterprises are monitoring their IoT networks constantly, up from 49%, and a record number of enterprises (69%) have a pre-emptive, proactive approach to IT security and network management. It’s time enterprises consider every identity a new security perimeter, including IoT sensors, smart, connected products, and the on-premise and cloud networks supporting them. Enterprises need to pursue a “never trust, always verify, enforce least privilege” approach and are turning to Zero Trust Privilege (ZTP) to solve this challenge today. ZTP grants least privilege access based on verifying who is requesting access, the context of their request, and ascertaining the risk of the access environment. Designed to secure infrastructure, DevOps, cloud, containers, Big Data, and scale to protect a wide spectrum of use cases, ZTP is replacing legacy approaches to Privileged Access Management by minimizing attack surfaces, improving audit and compliance visibility, and reducing risk, complexity, and costs for enterprises. Leaders in this field include Centrify for Privileged Access Management, Idaptive, (a new company soon to be spun out from Centrify) for Next-Gen Access, as well as CiscoF5 and Palo Alto Networks in networking.

  • Analytics and security dominate enterprise’ IoT management plans this year. 66% of enterprises are prioritizing analytics as their highest IoT data management priority this year, and 63% an actively investing in IoT security. The majority are replacing legacy approaches to Privilege Access Management (PAM) with ZTP.  Enterprises competing in healthcare and financial services are leading ZTS’ adoption today, in addition to government agencies globally. Enterprises investing in Lifecycle management solutions increased 11% between 2017 and 2018. Please click on the graphic to expand to view specifics.

Roundup Of Cloud Computing Forecasts, 2017

  • Cloud computing is projected to increase from $67B in 2015 to $162B in 2020 attaining a compound annual growth rate (CAGR) of 19%.
  • Gartner predicts the worldwide public cloud services market will grow 18% in 2017 to $246.8B, up from $209.2B in 2016.
  • 74% of Tech Chief Financial Officers (CFOs) say cloud computing will have the most measurable impact on their business in 2017.

Cloud platforms are enabling new, complex business models and orchestrating more globally-based integration networks in 2017 than many analyst and advisory firms predicted. Combined with Cloud Services adoption increasing in the mid-tier and small & medium businesses (SMB), leading researchers including Forrester are adjusting their forecasts upward. The best check of any forecast is revenue.  Amazon’s latest quarterly results released two days ago show Amazon Web Services (AWS) attained 43% year-over-year growth, contributing 10% of consolidated revenue and 89% of consolidated operating income.

Additional key takeaways from the roundup include the following:

  • Wikibon is predicting enterprise cloud spending is growing at a 16% compound annual growth (CAGR) run rate between 2016 and 2026. The research firm also predicts that by 2022, Amazon Web Services (AWS) will reach $43B in revenue, and be 8.2% of all cloud spending. Source: Wikibon report preview: How big can Amazon Web Services get?
Wikibon Worldwide Enterprise IT Projection By Vendor Revenue

Wikibon Worldwide Enterprise IT Projection By Vendor Revenue

Rapid Growth of Cloud Computing, 2015–2020

Rapid Growth of Cloud Computing, 2015–2020

Worldwide Public Cloud Services Forecast (Millions of Dollars)

Worldwide Public Cloud Services Forecast (Millions of Dollars)

  • By the end of 2018, spending on IT-as-a-Service for data centers, software and services will be $547B. Deloitte Global predicts that procurement of IT technologies will accelerate in the next 2.5 years from $361B to $547B. At this pace, IT-as-a-Service will represent more than half of IT spending by the 2021/2022 timeframe. Source: Deloitte Technology, Media and Telecommunications Predictions, 2017 (PDF, 80 pp., no opt-in).
Deloitte IT-as-a-Service Forecast

Deloitte IT-as-a-Service Forecast

  • Total spending on IT infrastructure products (server, enterprise storage, and Ethernet switches) for deployment in cloud environments will increase 15.3% year over year in 2017 to $41.7B. IDC predicts that public cloud data centers will account for the majority of this spending ( 60.5%) while off-premises private cloud environments will represent 14.9% of spending. On-premises private clouds will account for 62.3% of spending on private cloud IT infrastructure and will grow 13.1% year over year in 2017. Source: Spending on IT Infrastructure for Public Cloud Deployments Will Return to Double-Digit Growth in 2017, According to IDC.
Worldwide Cloud IT Infrastructure Market Forecast

Worldwide Cloud IT Infrastructure Market Forecast

  • Platform-as-a-Service (PaaS) adoption is predicted to be the fastest-growing sector of cloud platforms according to KPMG, growing from 32% in 2017 to 56% adoption in 2020. Results from the 2016 Harvey Nash / KPMG CIO Survey indicate that cloud adoption is now mainstream and accelerating as enterprises shift data-intensive operations to the cloud.  Source: Journey to the Cloud, The Creative CIO Agenda, KPMG (PDF, no opt-in, 14 pp.)
Cloud investment by type today and in three years

Cloud investment by type today and in three years

AWS Segment Financial Comparison

AWS Segment Financial Comparison

  • In Q1, 2017 AWS generated 10% of consolidated revenue and 89% of consolidated operating income. Net sales increased 23% to $35.7 billion in the first quarter, compared with $29.1 billion in first quarter 2016. Source: Cloud Business Drives Amazon’s Profits.
Comparing AWS' Revenue and Income Contributions

Comparing AWS’ Revenue and Income Contributions

  • RightScale’s 2017 survey found that Microsoft Azure adoption surged from 26% to 43% with AWS adoption increasing from 56% to 59%. Overall Azure adoption grew from 20% to 34% percent of respondents to reduce the AWS lead, with Azure now reaching 60% of the market penetration of AWS. Google also increased adoption from 10% to 15%. AWS continues to lead in public cloud adoption (57% of respondents currently run applications in AWS), this number has stayed flat since both 2016 and 2015. Source: RightScale 2017 State of the Cloud Report (PDF, 38 pp., no opt-in)
Public Cloud Adoption, 2017 versus 2016

Public Cloud Adoption, 2017 versus 2016

  • Global Cloud IT market revenue is predicted to increase from $180B in 2015 to $390B in 2020, attaining a Compound Annual Growth Rate (CAGR) of 17%. In the same period, SaaS-based apps are predicted to grow at an 18% CAGR, and IaaS/PaaS is predicted to increase at a 27% CAGR. Source: Bain & Company research brief The Changing Faces of the Cloud (PDF, no opt-in).
60% of IT Market Growth Is Being Driven By The Cloud

60% of IT Market Growth Is Being Driven By The Cloud

  • 74% of Tech Chief Financial Officers (CFOs) say cloud computing will have the most measurable impact on their business in 2017. Additional technologies that will have a significant financial impact in 2017 include the Internet of Things, Artificial Intelligence (AI) (16%) and 3D printing and virtual reality (14% each). Source: 2017 BDO Technology Outlook Survey (PDF), no opt-in).
CFOs say cloud investments deliver the greatest measurable impact

CFOs say cloud investments deliver the greatest measurable impact

Cloud investments are fueling new job throughout Canada

Cloud investments are fueling new job throughout Canada

  • APIs are enabling persona-based user experiences in a diverse base of cloud enterprise As of today there are 17,422 APIs listed on the Programmable Web, with many enterprise cloud apps concentrating on subscription, distributed order management, and pricing workflows.  Sources: Bessemer Venture Partners State of the Cloud 2017 and 2017 Is Quickly Becoming The Year Of The API Economy. The following graphic from the latest Bessemer Venture Partners report illustrates how APIs are now the background of enterprise software.
APIs are fueling a revolution in cloud enterprise apps

APIs are fueling a revolution in cloud enterprise apps

Additional Resources:

CIO’s Guide To The New Economics Of Real-Time Integration

CEOs’ decisions today to pursue digital-first strategies for greater revenue growth are defining their company’s competitive strengths in the future. CIOs and their teams are being challenged to drive a larger percentage of revenue growth in 2017 than ever before by providing IT-based insights daily.

  • Enabling faster revenue growth, improving products and replacing obsolete technologies are the top three CEO priorities have for CIOs in 2017.
  • 42% of CIOs say “digital first” is their company’s go-forward strategy for IT investments in 2017 and beyond.
  • 33% of CIOs consider revenue growth as their primary metric for measuring success with their digital business strategies.

The New Economics Of Real-Time Integration

IT teams are taking on the challenge by concentrating on those areas that can scale the quickest and deliver measurable revenue results. They’re finding that the integration approaches taken in the past don’t match the speed that customers, sales, suppliers and senior management need today. A key takeaway from CIOs’ initial efforts includes the finding that making small improvements in data latency can increase sales win rates in 90 days or less while improving cost controls.  Improving data latency is one of the key factors driving the new economics of real-time integration, which is defined below.

  • Integrations’ Inflection Point Has Arrived – Digital-first initiatives for defining new channel, selling and product strategies require more speed than batch-oriented integration can deliver. Customers now expect real-time response across all sales and support channels on a 24/7 basis. The pressure to drive greater revenue through digital channels and deliver a consistently great customer experience are forcing an inflection point of integration technologies today.
  • Batch-oriented approaches to integration fit well in an era of transaction-centric IT. Asynchronous, tightly-coupled, and relying on ETL for moving data around an enterprise network, these approaches were better suited for more predictable revenue strategies.  In contrast, going after new digital channels is unpredictable and requires real-time integration to deliver excellent customer experiences. Service-oriented frameworks that support synchronous data consumption and have low latency are emerging as a better choice for digital-first revenue strategies. Based on loosely-coupled integration points, these frameworks are capable of quickly adapting to new business requirements. Companies including enosiX are revolutionizing services-oriented frameworks by removing the roadblocks legacy integration approaches created.  The following graphic illustrates integrations’ inflection point and how past approaches to integration are giving way to more synchronous, loosely- coupled service-oriented frameworks capable of scaling faster to drive greater revenue.

  • And it’s fueling faster development cycles, reducing time-to-market and improving app and web services quality. The apps, web services, and APIs needed to launch a digital-first strategy don’t exist off-the-shelf, ready to be deployed for the majority of companies. Every company needs to create customizations to existing apps and web services, or create entirely new ones to support digital revenue strategies. Availability of real-time data through service-oriented frameworks is revolutionizing how apps, web services, and customizations get built. With real-time data designed in, it’s possible to test new apps across more use cases and ensure higher quality too.
  • While also enabling IT teams to exceed stakeholder expectations and their goals for digital-first strategies. Integrations’ inflection point is the most visible in how CIOs are now considered more responsible for revenue than ever before. From the initial revenue strategy definition through project managing apps and web services to delivery and producing revenue, CIOs and their teams who see themselves as business strategists excel in their roles. IT teams and the CIOs who lead them are seeing signs of integration’s inflection point every day. They’re seeing just how urgent the inflection point is, and how it’s redefining the economics of how they orchestrate systems together to attain revenue growth.  The insights and expertise CEOs, VPs of Channel Strategy, Marketing, Cloud & IT Infrastructure, and other senior management team members have needed to get quickly translated into apps, web services and digital first strategies that capitalize fast on new opportunities. Only through the use of service-oriented frameworks that can scale to support new revenue processes can any company compete in 2017 and beyond.

 

Five Reasons Why Every CIO Needs An Integration Roadmap In 2017

The difference between CIOs who lead and those caught in never-ending reactionary cycles is often a strategic IT plan and integration roadmap. It’s the CIOs who take the time to create and pursue an integration roadmap that has the greatest chance of breaking out of always reacting to IT projects and leading them instead. That’s because the majority of inbound requests center on data, reports or analysis only deliverable by integrating two or more systems together.

Five Ways Integration Roadmaps Are Putting CIOs Back In Control

Based on conversations with CIOs across a variety of industries including manufacturing, distribution, aerospace, financial services, and retailing, five factors emerged that led to creating integration roadmaps and getting in control of IT spending and priorities. I’ve summarized these five factors below:

  1. Integration roadmaps are proving to be an effective catalyst for driving purpose-optimized integration strategies, reducing middleware costs in the process. CIOs who create and continually improve their integration roadmaps are prioritizing purpose-optimized integration strategies to more efficiently scale global operations. Creating real-time integration links between SAP and Salesforce is one example of how CIOs are using purpose-driven integration to reduce customer response times for information, improving customer satisfaction in the process.  Enabling real-time, bi-directional data updates without requiring complex middleware coding and mapping of data is a challenging task, and innovative startups including enosiX are excelling in this area today.
  1. Defining a path for reducing ETL spending and dependence on logs to troubleshoot errors and measure performance.Reducing their dependence on ETL is giving CIOs and their teams much more flexibility in how they manage IT It is also freeing up system analysts to work on new projects instead of troubleshooting integration issues. With no automated error handling or recovery mechanisms, many CIOs are gradually phasing ETL out for more modern integration technologies that eliminate error logs altogether.
  1. Investing in the latest technologies that enable business process and application logic is making IT more responsive, helping them break out of a bureaucratic reputation. When I asked CIOs about the best way to increase responsiveness to internal customers, they wanted integration technologies capable of scaling across the back office and selling systems to make them more responsive. By having integration technologies that enable business process and application logic, the time-consuming, and often error-filled, the task of enabling new business processes manually goes away. And, when IT can react faster, their bureaucratic reputation is also on the way out too.
  1. Choosing to reduce and eliminate hand-built adapters and connectors from their IT infrastructures to free up support funds and time on urgent IT project needs today. One large-scale industrial equipment manufacturer has a staff of software developers and engineers who do nothing but keep adapters and connectors written in ABAP running across their ERP, Manufacturing Execution Systems, quality management, and supply chain systems. With production centers in the Midwestern US, China, and Europe, the ABAP team is always busy but never innovating. They are just ‘keeping the lights on.’ Having an integration roadmap is going to get this manufacturer out of the situation they are in today, which is draining dollars and time from IT.
  1. Move closer to quantifying the value IT delivers by showing how an integration roadmap provides support for cutting maintenance costs, consolidating apps and introducing new platforms. The ROI of IT often hinges on how effective CIOs are at reducing costs and still delivering a median or average level of service. By having a plan in place to attack integration challenges and costs, CIOs can immediately prioritize steps to improve service, reduce costs, and attain department and corporate goals.

Originally published on the enosiX blog, Five Reasons Why Every CIO Needs An Integration Roadmap In 2017. 

2013 ERP Prediction: The Customer Takes Control

From the obvious to the outrageous, enterprise software predictions often span a wide spectrum at the beginning of every year.

In enterprise software in general and ERP specifically, there are many safe harbors to dock predictions in, from broad industry consolidation to Oracle buying more companies.  Or the inexorable advances of cloud computing and SaaS platforms in ERP today, which is often cited in enterprise software predictions.

Too often predictions gravitate too much towards theoretical economics, overly-simplified industry dynamics and technologies, leaving out the most critical element: customers as people, not just transactions.  So instead of repeating what many other industry analysts, observers and pundits have said, I am predicting only the customer side of ERP advances in the next twelve months.

The following are my predictions for ERP systems and enterprise computing in 2013:

  • The accelerating, chaotic pace of change driven by customers will force the majority of Fortune 500 companies to reconsider and refine their ERP and enterprise computing strategies.  Social, mobile and cloud computing are combining to provide customers with more acuity and articulation of what their preferences, needs and wants are.  The majority of ERP systems installed today aren’t designed for managing the growing variation and pace of change in customer requirements and needs.  In the next twelve months this trend will force the majority of Fortune 500 companies to re-evaluate their current ERP systems when it becomes clear their existing enterprise systems are getting in the way of attracting new customers and holding onto existing ones.
  • Highest-performing CIOs will rejuvenate monolithic, dated ERP systems and make them agile and customer-focused, while at the same time excelling at change management.  There are CIOs who can handle these challenging tasks, and the future belongs to those who can fluidly move between them quickly.  In twelve months, a group of CIOs will emerge that are doing this, delivering significant gains to gross margins and profitability in their companies as a result.  They’re the emerging class of rock stars in IT and enterprise computing.
  • Quality ratings of ERP systems by internal customers will become commonplace, including 360-degree feedback on ERP performance.  This is overdue in many companies and it takes a courageous CIO and senior management staff to value feedback on how their ERP systems are performing.  In the most courageous companies, within twelve months the results of these internal surveys will be posted on bulletin boards in IT and throughout IT services departments.  For some companies this will be first time IT staff members have a clear sense of just what internal customers need, how they are being served, and what needs to be done to improve business performance.
  • ERP systems built on a strong foundation of personas, or clear definition of customers and their roles, will overtake those built just on features alone.  This is already happening and it will accelerate as featured-based ERP systems prove too difficult to be modified to reflect the fast-changing nature of personas and roles in organizations.  The quickest way to determine if a given ERP system launching in the next twelve months will succeed or not is asking what personas it is based on and why.
  • Customers push speed and responsiveness from a “nice to have” to a “must have” as advances in mobility platforms and integration make real-time possible.  If there is one unifying need across the personas of customers an ERP system serves, it is the need to improve responsiveness and speed. The same holds true within enterprises today as well. It would be fascinating to look at the data latency differences between market leaders versus laggards in the airline industry for example.  Customers will push accuracy, speed and precision of response up on the enterprise computing agenda of many companies this year. Speed is the new feature.
  • What were once considered ERP-based operations bottlenecks will be shown  to be lack of customer insight.  Take for example the very rapid product lifecycles in retailing.  At first glance slower sales are attributed to not having the right mix of products in stores, which is a classic supply chain problem.  Yet customer-driven ERP systems will tell retailers a different story, showing how product selection, even suppliers, are no longer pertinent to their customers’ preferences and needs.  More customer-centric ERP systems will help retailers overcome costly and difficult to recover from bottlenecks in their operations.

 Bottom line: Enterprises clinging to monolithic, inflexible ERP systems need to re-evaluate how their enterprise computing strategies are serving their customers before their competitors do.

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