Digital Systems – ‘To Integrate or Not to Integrate’

Organisations across all sectors strive to implement a Target Operating Model (TOM), or several, to support efficient, transparent, and effective delivery. At the heart of this, for optimal operation, is technology, and more specifically, the infrastructure and software that support the model. This often leads to the question: "Should we integrate these systems, or should we create a unified data warehouse?"

In this blog, we'll explore the questions to ask before choosing, as well as the pros and cons of each approach.

Most organisations have a well-developed strategic plan or growth strategy to support the business's long-term evolution. This is often tied to key milestones and objectives, creating a holistic approach where all key stakeholders are aligned, and business performance can be measured.

This is excellent, but how does your digital strategy fit in? The digital element is typically an overarching strategy that enables each key functional area of the business to operate digitally together. In essence, this digital and data strategy enables the main strategic plan. It clarifies how technology and data will specifically contribute to achieving the overall business goals. It's less about direct market engagement and more about powering the market approach and internal operations.

So, before deciding whether to integrate systems, we need to understand our overall plan and ask ourselves the following questions (this list is not exhaustive):

• What is the current state of our digital infrastructure (e.g., systems, platforms, tools)?
• What are the current pain points or inefficiencies in our processes that digital or data solutions could address?
• How are employees currently using digital tools and data in their roles?
• How will different business units or functions (e.g., marketing, operations, finance) benefit from or contribute to the digital and data strategy?
• What do customers or end-users expect regarding digital experiences or data-driven services?
• What types of data (e.g., customer, operational, financial) are most critical to our business goals?
• What are our current data privacy, security, and compliance requirements (e.g., GDPR)?
• How can we leverage advanced technologies like AI, machine learning, or big data analytics to extract value from our data?
• Do we have the right talent and skills in-house to execute the digital and data strategy?
• How can digital and data strategies enhance the customer experience (e.g., personalisation, faster service)?
• What are the digital expectations of our target market or customer segments?
• What is the budget available for developing and implementing the digital and data strategy?
• How will we prioritise investments in technology, talent, and infrastructure?
• How will the strategy position the organisation to adapt to future technological advancements?

By answering these questions, or a similar, more detailed set, you'll gain a sense of how your existing and potentially new systems need to interoperate and deliver actionable data insights.

Firstly, what is software system integration? It's the process of connecting different software applications, systems, or components to work together seamlessly, enabling data sharing, process automation, and unified functionality. It involves combining disparate systems into a cohesive ecosystem that supports organisational goals. This can be achieved through a few different methods, such as:

• API integration: Systems communicate through Application Programming Interfaces (APIs), allowing standardised data exchange.
• Point-to-Point Integration: Each system is directly connected to another via custom interfaces. Suitable for simple integrations but becomes complex with multiple systems.
• Middleware Integration: Uses middleware (e.g., ESB, iPaaS) as an intermediary layer to facilitate communication between systems.

The Pros

This approach is often used to improve operational efficiency while reducing, if not eliminating, the risk of errors. Additionally, system integration provides data consistency, both future-proofing data and providing better data for effective decision-making. Finally, it supports improved organisational and system scalability and offers an improved platform from which innovation can be leveraged.

The Cons

This can become a very complex and expensive project (or series of projects) if your software landscape is large (many different applications) and has high levels of legacy systems. You must also consider data security and privacy risks, as data is shared in real-time, the target system(s) must have robust security configurations. Finally, you must ensure your integration framework can support system updates (typically major) and data structure changes, or the entire system could fail.

 So, what is a data warehouse? It's a centralised repository designed to store, manage, and analyse large volumes of structured and semi-structured data from various sources across an organisation. It supports business intelligence (BI), reporting, and data analytics, enabling improved tactical and strategic decision-making. The first question to ask is: Where should my data live? The options are:

• On-Premises: Hosted on local servers (e.g., Oracle, SQL Server). Offers control but requires significant infrastructure.
• Cloud-Based: Hosted on cloud platforms (e.g., Snowflake, Amason Redshift, Google BigQuery). Scalable, cost-effective, and easier to maintain.
• Hybrid: Combines on-premises and cloud for flexibility. Consider factors like scalability, cost, and security requirements.

The Pros

You can create a unified data environment, without the complexity of integrating systems, that consolidates data from disparate sources into a single source of the truth, reducing silos and inconsistencies. This approach also streamlines data access for analysis, reducing time spent on manual data collection and preparation, and lowering the operational cost of supporting decision-making. Finally, it enables personalised marketing, customer segmentation, and improved experiences by analysing unified customer data, which can potentially drive competitive advantage.

The Cons

The initial setup costs, especially for on-premises solutions, can be high and will require specialist resources. Since this approach involves Extracting, Transforming, and Loading (ETL) data, the source data taxonomies will require alignment, at least initially, which could be difficult with poor and/or legacy systems. It will require ongoing maintenance and governance from more specialised resources than integration.

 As mentioned at the beginning, choosing between software system integration and a unified data warehouse for your digital and data strategy means weighing distinct pros and cons. The decision depends on your goals, data needs, budget, and operational requirements. Yep, it’s never easy!

In brief, choose system integration if your priority is real-time operational efficiency, cross-system workflows, or seamless application functionality. Choose a unified data warehouse if your focus is on analytics, reporting, and strategic decision-making with historical and aggregated data.

In many cases, organisations use both, integration to connect systems for real-time operations (e.g., APIs linking CRM and ERP) and data warehousing to aggregate data from integrated systems for analytics. This hybrid approach leverages the strengths of both but requires careful planning to avoid redundancy and ensure compatibility.

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