Top Three Benefits of a Business Analyst For Your AI Initiatives
Technology initiatives have long proven challenging for organizations of all sizes. The transition of implementing manual systems and tools to digital ones necessitated the role of the Business Analyst. But many organizations still forego, misunderstand the role, or don’t give the Business Analyst the tools or opportunities to make the business impact they can.
As organizations begin looking at investing in third party AI tools, or developing their own in-house, investing in a Business Analyst is a vital pre-requisite to both ensuring the success of the project as well as seeing the potential benefits of the tool.
Third parties do not understand the organization’s business objectives. And are sometimes at cross-purposes, especially when it comes to data sharing / results storing. And internal IT teams are often focused on IT’s objectives. The Business Analyst’s job is to coordinate the IT initiatives with the business.
Considering AI initiatives have the potential to be game changing for a business, the Business Analyst is crucial to be involved.
There are many reasons why Business Analysts are crucial to the success of an organization’s AI initiatives, but here are my top 3.
Alignment to Business Objectives
Business objectives are more than just a reframing of the organization’s mission statement. Business Objectives encompass the organization’s interests in total. The organization’s overall mission, income objectives, priorities for expense reductions, its assets including its data, even the organization’s culture are all part of the Business Objectives of an organization.
Many of these Business Objectives are not translatable to a third party AI tool or developer with a Powerpoint. Nor are they necessarily all in the purview of the internal IT developers. I’m yet to meet a Data Analyst or Database Administrator who wouldn’t throw more of a company’s resources at collecting, storing, and cleaning more data. There’s ALWAYS more data.
A Business Analyst both understands these objectives and, most importantly, sees to it the AI initiative aligns with these objectives. The Business Analyst can ensure the data available within the organization is sufficient for the AI tool to perform to its (advertised) potential, actually reaches the operations and stakeholders it is likely to best serve in the interest of increasing the quality of customer experience and increasing profits, can objectively test the impact of the AI initiative on the organization, and can ensure the organization receives and stores data from the AI results useful for the business going forward.
Change Management
AI initiatives provide unique challenges to change management within an organization. And Business Analysts are trained in effective change management.
AI is more than just a buzzword in the business community. For many stakeholders in an organization, it evokes fear of job loss or worse, Terminator. And AI automation can replace menial tasks. To a programmer or executive, this can sound incontrovertibly positive. But for some workers, there can be feelings of self-worth attached to these menial tasks, making change management exceptionally difficult.
And then there is the way AI can work with, or replace, processes within the organization. A business analyst can make sure these integrations happen without unintended consequences, by analyzing the affected stakeholders and mapping the process and its auxiliary systems. Managing these changes in an organization, and communicating them to IT and other stakeholders, are as critical as change management with the individuals responsible for utilizing the new processes.
What about customer-facing AI initiatives? While there will often be UX professionals managing the experience changes for customers, being cognizant of how changes in processes will effect customers is something the Business Analyst will be aware of and can make sure is being addressed by specialists in UX, marketing, graphic design, and so on. The customer is the most important stakeholder in any organization. The Business Analyst can ensure their needs are prioritized.
Hidden Opportunities in AI
While there are more important reasons in the present, I believe preparing for the future has so much value, and is so underrepresented in most AI initiatives, as to warrant being the third most important reason for having a Business Analyst on your team during the launching of an AI initiative.
Business Analysts can find hidden opportunities for AI in multi-step processes that otherwise will be missed. Business Analysts are trained in end-to-end process mapping, and when done in the context of AI initiatives, with a strong understanding of AI’s capabilities, discovery of how multiple tools, or the use of a single tool at multiple times in a complex process, can bring exponential returns. Process mapping gives a holistic view of the operation from end-to-end and makes it possible to identify where the benefits of AI can be applied. This is as opposed to a third party AI tool vendor or internal IT resource looking specifically at a problem to be solved.
There are hidden opportunities in the data AI tools can provide. For example, semantic analysis of communications can provide data attached to each communication an organization can leverage beyond the tool itself. When the tool is being built internally, a Business Analyst should be involved to make sure data related to business objectives is being generated and stored so data analysts and future machine learning initiatives may be able to utilize it. And third party AI tools can sometimes be hesitant to share their data output with their customer. This is something needing to be negotiated during the process of contract negotiations. As an organization leader, one can not assume either the data will be shared or the data not being shared will not be useful in the future.
A quick anecdote from my own past. A client had hired a third party AI tool with the objective of creating a predicted metric otherwise only available only from a small number of retail customers surveyed. The tool was collecting dozens of additional datapoints but the organization was not putting these to use. Additionally, the database produced was not being stored locally so data was being owned totally by the third party vendor after a prescribed amount of time had passed. Lastly, there were crucial datapoints not being included in the data allowing for Data Analysts to match this database with independent internal databases.
As a Business Analyst only brought in after the tool had been launched and implemented, I was unable to effect change for the data being generated by the tool. But I was able to leverage the data in the creation of an internal ML tool automating a crucial auxiliary objective of the organization, leading to improvements in experience of both internal stakeholders and end-customers.
Without the skill-set of knowing how to analyze the data available and then align that data to business objectives, the opportunity would have remained hidden.
One More Thing
As an additional note, a very close “fourth” is ROI analysis of an AI initiative. While third party AI vendors and internal IT teams can have either overly optimistic, or overly narrow, perceptions of ROI, an experienced Business Analyst will be able to more accurately report on the potential financial impacts of an AI initiative. Allow your organization to be protected of misinformed ROI projections by having a Business Analyst perform an objective ROI Analysis.
I’ll write in the future on the differences in ROI Analyses for AI initiatives as compared to traditional IT projects.
Conclusion
The Business Analyst is as important to the present and future success of an AI initiative as anyone else on an organization’s team. While some IT leadership and Product Managers will have some of the skills necessary to ensure the initiative’s success, a Business Analyst is an organization’s best resource to making its AI investment pay off.
