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To provide you with not only neutral information but also expert opinions, we consulted our Chief Product Officer (CPO), Adrien Deyhim, for his insights on these trends.
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Keeping up with the rapid pace of Business Intelligence (BI) and the vast tools landscape can be overwhelming and increasingly complex. As 2023 comes to an end, looking toward 2024, we wrapped up the trends of the market, and give you a glimpse of what the future of business intelligence might hold.
As solutions and needs have shifted, and because the world of software is not just made of AI, new analytics and business intelligence trends may emerge without you seeing them. Challenges in current delivery models may necessitate solutions that are more thoughtfully tailored by use case, self-service models may continue to evolve to meet user needs, a growing emphasis on embedded analytics may expand the capabilities of more work environments, and companies may look for new ways to leverage large language models (LLMs).
As the role of BI expands, so too does the complexity of the solutions that business ideas increasingly rely on to inform data-driven decision-making. As BI trends, it can be important for providers and users to be aware of the shifting landscape that these solutions exist in. That’s why we’re exploring five trends for business intelligence (BI) in 2024. Let’s jump in.
#1 Variety of user personas - governance and use case challenges
As the market for BI tools grows and more companies adopt business intelligence solutions, perhaps it isn’t surprising that analytics and business intelligence solutions see carried uses across industries and applications. The need for effective and capable BI solutions may be driven in part by an increasing focus on data-informed decision-making across many companies. As BI tools become more capable and continue to offer expanded features, businesses can find a growing number of uses for them.
The analytics and business intelligence (ABI) platforms attract a wide range of users with different personas. These multi-persona users include analytics developers, business analysts, augmented consumers, and data scientists, each utilizing ABI tools for their specific needs and objectives.
This phenomenon necessitates the evolution of more comprehensive ABI solutions that seamlessly integrate capabilities from both data science and machine learning platforms. However, with the proliferation of multiple ABI platforms within organizations, a growing concern is emerging in terms of governance.
The introduction of various platforms and the diverse utilization of ABI tools by different teams to define metrics with their unique business logic raise governance challenges, emphasizing the need for effective management and oversight in this multifaceted BI landscape.
Adrien Deyhim,
Toucan Chief Product Officier:
"I don't think it's beneficial for a product to become "comprehensive" for all personas. It usually fleshes out the product, making it more complex and diluting the design. In particular, I disagree on the value of blending data science use cases with analytics use cases. Unless they're different products within the same suite, but then again I don't see the point of rating a suite rather than a tool within the suite.
They talk a lot about multi-persona, but it's more of a use case-oriented approach, with potentially several personae working together. In my opinion, they confuse use case and persona (as can be seen at the end of their study)."
#2 Meeting Self-Service Challenges
Another key trend in 2024 may hinge on BI tool providers finding ways to address challenges in self-service tools. One chief challenge for many providers may be the adoption of self-service tools. As business intelligence solutions become more capable and integrations become more common, one might have expected to see self-service proliferate more widely than it has so far. The landscape of business intelligence is witnessing a notable shift as organizations express dissatisfaction with the unmet expectations of self-service analytics.
The conventional belief that self-service would seamlessly deliver business value has fallen short, prompting a demand for more prebuilt analytics content. Organizations are recognizing the limitations of self-service in meeting user expectations and are actively seeking solutions that offer a more comprehensive and efficient approach. The trend indicates a growing emphasis on prebuilt analytics content to better serve users, reflecting a strategic pivot in the business intelligence arena towards more robust and ready-to-use analytical tools.
As one of the drives to the adoption of self-service tools can be the promise of data accessibility, it can be important to find ways to meet the expectations of users through tools that offer ease-of-implementation across a wider range of user proficiencies and roles. Offering pre-built catalogs of content and pre-built templates, for example, can make it easier for users to effectively use self-service tools across a wider range of uses without the burden of excessive setup processes.
As BI tools see wider adoption and fill a wider range of roles and use cases, it can be important for providers to find ways to ensure that users can easily generate accurate visualizations and dashboards from relevant data. 2024 may see a trend of BI providers finding ways to enhance time to value through offering more template capabilities that can enable users to quickly generate useful reporting dashboards and embedded analytics.
Toucan Chief Product Officier:
"The fact that self-service should have taken off more and that we need to think more about pre-built content catalogs to include in a report but also pre-built templates. This is a recurring need among our customers."
#3 Embedding Analytics
As not only analytics and business intelligence tools, but their integration capabilities become more robust and complex, 2024 may be another year in which we see a trend of data democratization through the utilization of increasingly capable digital tools. One such integration, embedded analytics, may continue to serve an important role.
As data becomes more accessible and analytics tools become more capable, embedding analytics capabilities into a wider range of existing business tools may become a growing trend. The ultimate goal of data accessibility is to empower data-driven decision-making, often regardless of station. With embedded analytics, streamlining the process of data-informed action across departments and levels may be more accessible than ever.
With companies relying on a growing range of business tools, opportunities to streamline workflows can be highly impactful. Offering users a way to integrate actionable analytics into their enterprise solutions can be important. CRM, ERP, or in any software solution often aid in streamlining data and decision-making, so embedding analytics in these existing workspaces is often a natural next step.
Toucan Chief Product Officier:
"I think it's a good idea to be able to start or finish a data flow in a digital workspace (what I interpret as the flagship tools of the business). Analytics tools are just details in our users' daily lives, and it's better to integrate them where they spend most of their time."
#4 Making it Easier to Create - Prebuilt Analytics and Metrics
With the challenges faced in self-service adoption and growing ranges of use cases and needs, as well as a growing emphasis on embedded analytics, another trend we may see arise in 2024 is the adoption of BI tools that offer effective solutions to pain points such as these.
Catalogs of prebuilt metrics and analytics can make it easy to get started with effective insights. Considering that data accessibility is not only a common goal of BI tools but often a barrier to adoption as well, it may be important to find ways to enable users to effectively leverage their data without creating proficiency barriers or necessitating lengthy setup times. In addition to being challenges in ease of use, these can be challenges in time to value, creating a lengthier configuration period that users must persist through before they are able to harness the power of their data.
While the promise of BI is often accessibility and democratization of data across departments, teams, and roles, offering pre-built solutions can help enhance the usability of BI tools, making this a potential route that providers might explore as BI tools are used across a wider range of roles.
#5 LLMs and AI in BI - Challenges to Overcome
With one of the chief goals in the adoption of self-service solutions being data accessibility, it isn’t surprising that companies have begun to eye the capabilities of AI systems like large language models (LLM) in search of ways to leverage them for use in self-service analytics and business intelligence. However, AI, as an infant technology, faces its share of challenges. As companies continue to find new ways to leverage AI, another trend we may see in 2024 is finding ways to overcome some of the challenges of using AI in BI.
Some of these challenges may include finding ways to overcome accuracy concerns. One of the chief capabilities of LLMs is their ability to accurately understand queries. However, in order for LLMs to function effectively, they require reliable data to query. This entails having well-structured and clean tables, a strong naming convention, and a certain level of data maturity within your company. Implementing LLMs into self-service BI tools may necessitate the creation of systems that can consistently understand queries.
When considering self-service Business Intelligence, AI may initially seem like the perfect solution. Data professionals are tired of being the bottleneck, while business users crave for data-powered insights. Everybody dreaming of this single line of text that can create the charts they desire, until they actually have it in their hands. With this approach, we lose sight of an essential element: the objective of making data accessible to all business users is not relevant. Rather than allowing each individual to create their own visualizations, resulting in varying numbers and calculation methods, which undermines the objective of establishing a unified truth, it is more sensible to align all stakeholders around a single point of truth. This approach enables focused discussions on the decisions that need to be made, which is a fundamental belief held by the team at Toucan.
In reality, the major milestone AI could achieve for Business intelligence can be found in the structure, architecture, and preparation of data, which occur well before analytics and BI tools.
The Bottom Line
2024 will likely be an interesting year for 2024. As companies continue looking for ways to leverage data more effectively, democratization efforts may, in part, fuel the drive for self-service BI options, but there are still challenges in adoption that must be addressed for many companies.
As such, 2024 may see a shift in the way self-service tools are offered. Additionally, as analytics and business intelligence tools continue to serve an expanding range of use cases and roles, providers may focus their efforts on finding ways to more accurately tailor their services to meet various specialized uses while affording enhanced collaboration between types of users, often in different teams or departments.
Similarly, embedded analytics can help streamline data into existing workspaces, further aiding in decision-making. Offering more prebuilt solutions may be an important trend as BI providers work to meet self-service challenges, and companies may work to meet some of the many challenges facing AI in BI.
Remember, if you’re looking to enhance your customer-facing analytics, we’re here to help. Do more than just present data — tell a story. Toucan Toco’s embedded and customer-facing analytics can help you harness data effectively. To learn more or get started, get in touch today.
