Leaders Roundtable: Accelerating Your Outcomes: Smart Integration & Automation in Your Business

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Leaders Roundtable: Accelerating Your Outcomes: Smart Integration & Automation in Your Business

Business technology systems and platforms are increasing in complexity.

The past few years have seen business leaders embrace digital systems – implementing new systems and tools to rapidly solve business and customer challenges. But this investment has come with a cost, and creates challenges for tech teams:

  • Applications reside across multiple cloud environments – public and private
  • Data is scattered across many different silos, limiting opportunities for learning and insight
  • Security and customer privacy can be compromised by poor API and data management

Join your industry peers for this Digital Leaders Roundtable to learn how businesses are creating intelligent processes and applications; and reducing their technology complexity by securely connecting applications and data across any cloud or on-premises environment. During the discussion I will share Ecosystm’s independent research on AI and automation vendors – what is the market perception of the leading providers and why do buyers prefer these leaders?

During the roundtable, we will share and discuss:

  • How businesses are selecting Automation and AI technology partners
  • Practical examples of how organisations are using automation to integrate applications and systems across private and public clouds
  • Why businesses are moving from automating tasks to entire processes

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Leaders Roundtable: Why Organisations in New Zealand Fail to Maximise the Value of their Data

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Leaders Roundtable: Why Organisations in New Zealand Fail to Maximise the Value of their Data

Most organisations today continue to underutilise the data they generate, and struggle to deliver on business outcomes.

At the same time, they face multiple challenges – continuing supply chain disruptions; an ongoing energy crisis that has led to a strong focus on sustainability; economic uncertainty; skills shortage; and increased competition from digitally native businesses – where the effective use of data holds the answer!

Ecosystm research finds that in New Zealand:

  • Only 38% of organisations have Data & AI strategy as a key priority
  • 47% of organisations find it a challenge to secure budgets for Data & AI because they are unable to show business value
  • 56% of organisations do not have a well-defined data strategy that focuses on seamless access of real-time data across the organisation
  • 72% of organisations are still focused on building a central data repository despite the emergence of data fabrics

Join this Executive Leaders Roundtable to discuss how you can support your organisation’s evolving priorities, demonstrate the outcomes that your organisation wants to achieve, and build a futureproof data strategy that considers the context within which your business operates in Aotearoa New Zealand.

Discussion points will include:

  • How ready organisations’ current data strategies are for emerging trends such as ESG reporting and sustainability measures
  • How a robust technology platform can mitigate challenges through efficient data collection and verification, better forecasting, and scenario modelling, and automation
  • How cloud can be an enabler and at the same time meet Māori data sovereignty requirements
  • The importance of a data governance policy in driving a data-driven mindset?

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The Future of Business: 5 Ways IT Teams Can Help Unlock the Value of Data

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In the rush towards digital transformation, individual lines of business in organisations, have built up collections of unconnected systems, each generating a diversity of data. While these systems are suitable for rapidly launching services and are aimed at solving individual challenges, digital enterprises will need to take a platform approach to unlock the full value of the data they generate.

Data-driven enterprises can increase revenue and shift to higher margin offerings through personalisation tools, such as recommendation engines and dynamic pricing. Cost cutting can be achieved with predictive maintenance that relies on streaming sensor data integrated with external data sources. Increasingly, advanced organisations will monetise their integrated data by providing insights as a service.

Digital enterprises face new challenges – growing complexity, data explosion, and skills gap.

Here are 5 ways in which IT teams can mitigate these challenges.

  1. Data & AI projects must focus on data access. When the organisation can unify data and transmit it securely wherever it needs to, it will be ready to begin developing applications that utilise machine learning, deep learning, and AI.
  2. Transformation requires a hybrid cloud platform. Hybrid cloud provides the ability to place each workload in an environment that makes the most sense for the business, while still reaping the benefits of a unified platform.
  3. Application modernisation unlocks future value. The importance of delivering better experiences to internal and external stakeholders has not gone down; new experiences need modern applications.
  4. Data management needs to be unified and automated. Digital transformation initiatives result in ever-expanding technology estates and growing volumes of data that cannot be managed with manual processes.
  5. Cyber strategy should be Zero Trust – backed by the right technologies. Organisations have to build Digital Trust with privacy, protection, and compliance at the core. The Zero Trust strategy should be backed by automated identity governance, robust access and management policies, and least privilege.

Read below to find out more.

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Leaders Roundtable: The Need to Evolve Data Governance & Management

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The Future of Business: 7 Steps to Delivering Business Value with Data & AI

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In recent years, businesses have faced significant disruptions. Organisations are challenged on multiple fronts – such as the continuing supply chain disruptions; an ongoing energy crisis that has led to a strong focus on sustainability; economic uncertainty; skills shortage; and increased competition from digitally native businesses. The challenge today is to build intelligent, data-driven, and agile businesses that can respond to the many changes that lie ahead.

Leading organisations are evaluating ways to empower the entire business with data, machine learning, automation, and AI to build agile, innovative, and customer-focused businesses. 

Here are 7 steps that will help you deliver business value with data and AI:

  • Understand the problems that need solutions. Before an organisation sets out on its data, automation, and AI journey, it is important to evaluate what it wants to achieve. This requires an engagement with the Tech/Data Teams to discuss the challenges it is trying to resolve.
  • Map out a data strategy framework. Perhaps the most important part of this strategy are the data governance principles – or a new automated governance to enforce policies and rules automatically and consistently across data on any cloud.
  • Industrialise data management & AI technologies. The cumulation of many smart, data-driven initiatives will ultimately see the need for a unified enterprise approach to data management, AI, and automation.
  • Recognise the skills gap – and start closing it today. There is a real skills gap when it comes to the ability to identify and solve data-centric issues. Many businesses today turn to technology and business consultants and system integrators to help them solve the skills challenge.
  • Re-start the data journey with a pilot. Real-world pilots help generate data and insights to build a business case to scale capabilities.
  • Automate the outcomes. Modern applications have made it easier to automate actions based on insights. APIs let systems integrate with each other, share data, and trigger processes; and RPA helps businesses automate across applications and platforms.
  • Learn and improve. Intelligent automation tools and adaptive AI/machine learning solutions exist today. What organisations need to do is to apply the learnings for continuous improvements.

Find more insights below.

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