Integrated enterprise data is now one of the most important creators of opportunity in terms of how your business competes, meet customer needs, manage your operations and costs, and enable your employees. The best practices for harnessing the transformative power of big data include:
- Align information technology strategy, organisation and assets with business strategy and operational requirements.
- Capture transformative opportunities by designing an ecosystem that employs a federated – and virtualized – approach to data availability, and Artificial Intelligence (AI), to reshape everything from risk management to customer interactions.
- Establish a change program to lead the enterprise along the path toward proactive information maturity.
While the approach can be scaled to fit the organisation’s state of readiness and appetite for change, it should always incorporate these success factors. It is also crucial to understand that this is a journey. The initial choices about business priorities, solutions and enabling technology are crucial, but they are foundational and a starting point for continuous improvement.
Data is seen as the new oil, the element that will drive new forms of business models and new levels of organisational performance and design. Some enterprises have fully committed to realising the promise – Google, Facebook, Amazon, TikTok amongst the biggest and most obvious, but the massive majority struggle to extract value from data and use it to drive organisational change and strategic decision-making and performance.
Inevitably there are two sides to the issue. On the one hand the technology and data “ecosystem” have become massively more powerful and extensive. On the other hand, executive and organisational attitudes and behaviours, for the most part, find it hard to see the wood for the trees and therefore establish optimal responses; and also, while the technology is tremendously powerful – data storage, compute power, data management and analytics software – the reality is that the technology is not yet fully baked so as to provide truly holistic, architecturally coherent single stop solutions to an enterprise.
There are three key aspects to addressing this; selecting and managing the technology better by focusing more on robust and flexible frameworks – Data Asset Management approaches offer a lot in this regard; being up to date with and responsive to the evolving technology, while balancing the introduction of new with the challenges of the legacy environment; and then at the heart of the issue is the organisation itself – the way in which it thinks about and responds to the data opportunity and challenge. This first blog will start by trying to address this foundational issue – the way in which the enterprise can align itself and best exploit the opportunities of data.
Few organisations, and arguably none really in the financial services industry, have really begun to harness the potential of integrated, enterprise (big) data. Among the obstacles:
- The legacy technology environment is invariably complex, with multiple data sources, databases and systems that are not well linked.
- Scale requirements, costs and investment risk tend to expand.
- Siloed thinking about data and its application complicates data access and system updates.
- A disconnect often exists between user needs and IT capabilities.
- Technology strategy and the resulting infrastructure may be insufficiently linked to long-term strategic goals, and cross-enterprise data policy may be lacking.
- Lack of enough skilled people in the organisation – from programmers to skilled and thoughtful management.
What to do?
1). Align IT Strategy with Business Needs
The goal is to create a strategic path toward mature information behaviours and values, characterized by:
- Consistency based on a shared understanding of, and trust in, the data, systems and outputs
- Controls to ensure that the information has sustainable credibility and integrity
- Cross-functional transparency of the data
- Seamless data access of data for all interested and authorized groups
- Incentives for the proactive use and development of data, within the appropriate controls
We believe a structured process is critical to achieving a worthwhile strategic outcome. This process must align technology strategy with the business needs arising from the enterprise and business unit strategies. The starting point is to define what the business needs and opportunities are. This endeavor will be iterative and progressive. Important steps are:
- Ensure that your strategic and operational planning processes identify current and emerging technology needs. Planning should establish how the enterprise intends to win in each of its chosen markets, what capabilities will be required to win, and what technology platforms and functionalities will be needed to support those capabilities.
- Establish clear two-way communication between business leaders and the technology group. Start an ongoing discussion about how data is actually used by internal and external stakeholders and how technology could better meet business requirements. Look for shared needs that suggest efficient cross-enterprise solutions.
- Develop a first-cut information technology strategy as a basis for designing the right technology ecosystem. This strategy should present a vision for the delivery and use of data and information across the enterprise; provide an initial view of priorities and dependencies; define the required organisational enablers, including access, security and data integrity; and make the case for strategic investment.
2). Design a Technology Ecosystem to meet Business Needs
We define “technology ecosystem” as the coordinated set of internal and external resources that drives the creation and delivery of data and information for an organisation and its stakeholders. In other words, the ecosystem defines the data sources, platforms, applications and protocols that enable you to implement and refine your first-cut strategy. The hallmarks of success are:
- Ease of use
- A single, simple way for internal users to access, manipulate and present any of the data
- A simple, intuitive user interface to engage the account holder
- Extremely high performance and scalability, at reasonable cost and low risk
- Ability to access data from anywhere – without interfering with pre-existing technology
- Flexibility and scalability to accommodate future business needs and changing user requirements within the context of a single solution ecosystem
- Open-ended architecture, to better meet user requirements and help keep pace with rapid advancements in technology
- Integrated approaches to security, privacy, and storage
To achieve these hallmarks of a sound technology ecosystem, we recommend that you:
- Use a metadata approach to resolve questions of data quality and structure. (Metadata is data that provides information about other data to make a system easier to work with) We think using metadata, and defining data as sets of objects, is essential.
- Automate data discovery and tie this process to the object driven metadata approach.
- Adopt a federated approach to data, to enable pulling from multiple sources. Consolidating data in a virtual data lake can eliminate the need to build expensive data warehouses.
- Standardize data presentation, using pre-set data modules and a large library of presentation tools to pull data from the lake efficiently and effectively.
- Create a robust layer of predictive analytics, to better serve both internal constituencies (e.g., risk management, product development, operations, marketing and distribution) and external stakeholders (e.g., customers and partners). Advanced statistical approaches, modeling and artificial intelligence can generate enormous value from the data. These sophisticated analytics should be built as a layer on top of the foundational elements, so they can be easily updated.
- Put all of these within a Data Asset Management framework and ongoing management process.
3). Establish an Enterprise-Wide Change Programme
A well-designed technology ecosystem will do a lot for your enterprise. It will bring multiple data sources together, synthesizing and presenting data in the most appropriate format in near-real-time. It will enable employees to ask questions and model huge amounts of data, to integrate analytics with real-time processes, and to implement powerful predictive engines based on artificial intelligence. And it will begin to lower organisational silos by federating the approach to data.
That is when a more fundamental management challenge – and opportunity – emerges: under the light of well-structured information, everything changes. The historical process-driven, functionally focused needs are now joined by clearer high-level aspirations, for example:
- What are the essential cross-functional technology platforms that support our strategic objectives, and how do we optimize them?
- What will industry standard product and service delivery look like in 5–10 years, and how can we start working now to meet or exceed those benchmarks?
- Are we using the right mix of in-sourcing and outsourcing to implement our strategy?
- How do the answers to questions such as these change the requirements for our ecosystem?
- How should the broader enterprise change to support technology as a key enabler?
Success entails top-down and bottom-up adoption of a new paradigm for the discovery, manipulation and use of data. To get there, you need an enterprise-wide change program that will transform the organisation from one that may be struggling with the basic control and management of data to a team infused with the spirit of using data and information for transformational outcomes.
A path to maturity model (see figure below) can be your roadmap on this journey. It will help you understand where you are – and want to be – in terms of data management strategy, data governance, data quality, data operations, platforms and architecture.
One of the critical steps on the path to technological maturity is the formulation of an overall Information Orientation process.
- Define the formal basis for data and information to establish trust and understanding.
- Put in place consistent approaches to controlling data and information – to ensure data integrity as well as consistency of approach.
- Define performance criteria to ensure that data and information are shared.
- Encourage proactive innovation, within reasonable controls.
- Build enabling policies and procedures to support all of the above.
- Identify and communicate what is needed from other groups in the organisation to enable continuous improvement of information technology, including operational and process support, innovation, and management attention.
The benefits of a strategic approach to big data, and information technology in general, are extensive. This approach can create the conditions for radically transforming data and information in an enterprise. It can leverage the power of new technologies to deliver enormous competitive and user benefits. It can slash technology costs, and potentially even take out significant layers of costs within the business.
Through this journey, the organisation will progressively become more intelligent and self-aware. Success will require a game-changing strategic approach to how the organisation thinks about data and configures and manages its technology ecosystem. As a starting mindset, look at technology as a set of broadly defined products that can be used to endlessly reinvent the business.