The Nitty-Gritty of Self-Service Business Intelligence

As the old adage goes, a master of information is a master of the situation. This rule of thumb works in the sphere of business as well, since data on customers, dominating trends in the niche, and workflow indices of the company can become benchmarks for mapping out the marketing strategy of the organization for months to come. Realizing the paramount importance of such data and the benefits of its handling, enterprises invest in business intelligence (BI) software to leverage state-of-the-art tools for data collection, processing, and analysis.

Yet, if large organizations dealing with data science solutions have responsibilities that lie in the area of their IT personnel, for smaller ventures — and especially startups — such examples are quite rare because paying regular salaries to a whole technical department is far beyond their means. That is why they often search for the answer to the question “What is self-service business intelligence?” and try to implement the best self-service BI practices into their pipeline routines to successfully address the multitude of challenges they face. 

Self-Service Business Intelligence Explained

What is self-service BI? It’s the process of business data collection and analysis that is performed not by the IT specialists of an organization as it’s conventionally done, but by other teams like sales, accounting, product developers, marketing, etc. 

Is it possible for people with non-technical backgrounds and very basic computer skills? Yes, it is. The term “self-service business intelligence” embraces not only the analytical capabilities and procedures but also respective tools to set up such processes. Forward-looking software vendors trimming their sails to the latest trends in the realm tend to supply their BI solutions with some examples of self-service BI facilities. 

Typically, self-service business intelligence architecture contains a number of dashboards and interfaces that present no or very few challenges for laymen to come to grips with. Accordingly, specialists in the field of sales and marketing can execute queries and obtain insights from a plethora of data sources without addressing data analysts or the IT crew and then make data-driven business decisions. 

How is the self-service BI routine different from the regular one?

Traditional and Self-Service Business Intelligence Juxtaposed

In the classic BI cycle, all departments of an organization—from HR to sales—generate and hoard heaps of various business-related data. After it is collected, they pass it on to the IT team and/or BI specialists to perform data analysis and produce performance reports, predict developments, and envisage trends. And this is not a one-off instance. Such practice is repeated every now and then to support the standard pipeline operations of a venture.

In this way, the quality of data and analytics remains high but the overall efficiency of the enterprise is significantly hamstrung since the multitude of challenges and responsibilities thus piled upon the tech crew forces it to attend to too many errands at the same time. As a result, the performance is essentially delayed and stakeholders are kept fuming and waiting (sometimes for days) for reports to be delivered to them. At the same time, the trustworthiness and value of this data can drastically decrease during long delivery. 

Self-service business intelligence is a totally different story. Here, data end-users don’t have to remain in standby mode until the IT guys do their part of the work. Leveraging self-service BI tools, personnel of all departments make use of intuitive UI that will help them analyze data and produce reports without possessing profound technical expertise. The possible mistakes and inadequacies that may arise are a valid trade-off for the promptness of the procedure obtained via self-service business intelligence. The tech crew also has one more care off their hands and can pay closer attention to responsibilities that require their exclusive competence.

What perks does such an approach promise to a company?

The Benefits of Self-Service BI

Once implemented, self-service BI becomes a powerful asset to the organization because it:

• Promotes decision-making. No more wearisome and tedious attempts to bring together countless spreadsheets with the goal of figuring out the overall picture. Self-service BI dashboards and reports visualize all necessary data and allow both managers and rank-and-file personnel to map out knowledgeable steps in order to streamline business workflow.
• Grants universal access to data banks. An employee from any division can find the information useful for their responsibility sector. Thus, marketers develop insights into customer behavior and needs, financiers share reports related to their sphere, the HR department looks into personnel performance data, etc. 
• Provides the single version of the truth. The previous benefit translates into this one. Once all parts of the venture are supplied with identical dossiers, there will be no discrepancies between data so the corporate mechanism will function as a single body in a transparent work environment.
• Enables collaboration across the entire organization. When all staff members have equal access to data conveyed by self-service BI tools, they can create task force groups containing specialists from all departments who will contribute to the discussion of results and the shaping of company policies.
• Relieves pressure on IT and BI teams. Since end-users can handle data processing and analysis themselves, tech departments and analysts will direct their efforts to other assignments that demand their immediate attention. 
• Streamlines basic shop floor procedures. Creating specific tasks for each department becomes a breeze when all the input data you need are at your fingertips 24/7. Micromanagement is also considerably facilitated via employing self-service BI mechanisms.
• Awards competitive advantage. The robust usage of data, getting timely insights, and stepping up decision-making spells the spike in business’ efficiency of an organization and correspondingly a significant edge over rivals in the niche.

Despite evident merits, however, the implementation of self-service BI initiatives may face serious obstacles.

The Challenges of Self-Service Business Intelligence Employment

As seasoned players in the field of data handling, we at NIX United consider it essential to pay attention to the following bottlenecks while introducing self-service BI.

The Reluctance of End-Users

Both employees and managers who are used to conventional intuition-driven practices of adopting business decisions can resist onboarding self-service business intelligence. Furthermore, technically-handicapped personnel may find learning to operate self-service BI tools daunting if their UI isn’t user-friendly enough. 

This problem can be mitigated by consistent measures aimed at explaining and emphasizing the benefits of self-service solutions as well as optimizing them to be mastered by average users.

Inaccurate data processing results

Since such solutions are meant to be a universal tool for everyone (specifical laymen), odds are that analytics can be handled inadequately, producing poor results. Moreover, being entered by random people, data may become rather confused and erratic. 

All these pitfalls can be avoided by comprehensive training programs that will educate the staff not only to employ self-service BI software but also to search for necessary data and create reports and visualizations.

Endangered Data Privacy and Security

Because of the many endpoints and people who have access to business, financial, and personal data via self-service BI solutions, their integrity may be compromised if the system is not properly implemented.

To minimize data leakage or unauthorized penetration risks, strong security measures must be envisaged both at the stage of software development and while the tool is being utilized by stakeholders.

Rampant Deployment

Being much like an individual endeavor, a self-service business intelligence system can grow rather chaotic with multiple participants deploying such environments on their own. 

To prevent things from getting out of control, BI teams should monitor the deployment process and set some centralized limitations on standalone efforts by various users.

All of these challenges can be successfully addressed if self-service BI platforms are implemented according to a thought-out strategy with the support of specialists.

Enforcing Self-Service Business Intelligence: 5 Things to Remember

There are some fundamental considerations one must take into account while mapping out a self-service BI implementation plan:

• Define roles. You should assign responsibilities among stakeholders that will utilize the solution you are going to launch. This distribution depends on their functions in the organization as well as on the kind of data they deal with.
• Work out the onboarding strategy. You should realize that adopting any new technology with its specific features and characteristics takes time and effort. And when you let it proceed in its own way it will be even longer and harder. To propel it more swiftly, having and implementing a detailed training and onboarding policy is a must.
• Keep monitoring software employment. When you have kicked the self-service BI framework into action and made sure it operates in accordance with your expectations, don’t let up. You should keep track of the way it is used to make adjustments if some element underperforms.
• Prioritize user-friendliness. Since most users of the self-service BI solution are likely to be people with only elementary IT knowledge and skills, it’s mission-critical for the software to have an intuitive UI and be foolproof in handling.
• Mobile experience matters. Given the ubiquity of smartphones in the contemporary world, it is vital for your self-service BI solution to have a mobile version. This will not only contribute to its wider usage but will also make the data and analytics available for employees wherever they are. 

These are the basics, but each organization can add some more points to this list and develop its own tailor-made implementation scheme. No less important are the components of self-service BI architecture that should be included in the solution.

Must-Have Features of Self-Service BI Architecture

The examples of the existing self-service BI solutions display utmost flexibility in trying to cater to the requirements of the organization that employs them, yet some features are considered to be bread-and-butter for all of them.

1. Intuitive Drag-and-Drop Interface

A simple and uncluttered interface is the primary element of any solid self-service BI tool. It will allow users to master it quickly and easily navigate around the solution. They also must be able to pick data fields from the available tables and drag and drop them where they want. Plus, creating custom dashboards and accessing analytics should be performed in a few clicks to let non-tech personnel make smooth use of the tool.

2. Pre-Set Dashboard Templates

These embedded analytics tools are meant to visualize data patterns for easier comprehension and further analysis. Typically, such templates contain color-coded maps, pie charts, bar/line graphs, scatter plots and other media that enable data presentation. Here, drag-and-drop functionality should be employed, as well as data blending characteristics and database plugins.

3. Various Reporting Tools 

Reporting capabilities are also crucial for a top-notch self-service BI environment. Such tools should be able to analyze data presented in different formats (both visual and textual) depending on the type preferred for each purpose. These tools also must be made shareable via links so that all persons involved in data handling could see the reports on their dashboards supported by different gadgets.

4. Data Connectors

Today, the range of databases available for business users is quite large and a satisfactory BI solution must guarantee access to most of them. Examples of such data sources include the company’s CRM and ERP as well as Google Drive, Google BigQuery, Azure Synapse, Sharepoint, Microsoft Analysis Services, Microsoft SQL Server, etc. In case the customer wants to get connected to other platforms, the “in-memory data source” feature should be included in the solution to enable this option.

5. Integration Options

Since modern enterprises make extensive use of apps and other software in their routine pipeline, self-service BI solutions should be able to integrate all of them under one roof and provide the seamless flow of data and communication between systems, chats, projects, and tasks in which various departments are involved.

6. Advanced Technological Tools 

Tools powered by state-of-the-art know-how that is all the rage in the current IT-driven world can enhance the capabilities of any self-service BI environment. Here, it all depends on the expertise of the developer who can harness AI, cloud facilities, predictive analytics, natural language querying, ML, and other technologies able to augment the efficiency of the custom self-service BI solution they build for your organization.

Summing It up

With the penetration of digital technologies into an ever-growing set of domains, IT literacy becomes a must for non-tech personnel of any business wishing to outsell their rivals and expand into new consumer markets. Self-service business intelligence tools are an excellent example of such software enabling its users to perform numerous data-processing and analytical tasks without addressing the IT and BI departments of their companies. Contact us to develop a custom self-service BI tool for you.