The Inquisitive Project Manager

When I started teaching VoiceXML at Seneca College in Toronto, Canada years ago, I didn't realize I was embarking on a 4 year teaching career in AI. VoiceXML is a natural language speech recognition software, which involves automated voice communications. It's a feature-rich computer language for building interactive voice response (IVR) applications. Natural Language Processing (NLP) is a sub-field of AI where natural language data is processed and analyzed by computers. You may be familiar with ringing up any call centre, and receiving a voice chatbot asking you "Tell me what you want to do today." Algorithms detect your voice, and provide customer-friendly responses based on interpretation of your words. IVR systems discern intent, and can be used for a variety of services from banking transactions, to mobile purchases, online retail orders, and travel bookings. It begs the question, how can the business analyst have a space in the world of AI?

"Nothing is so painful to the human mind as a great and sudden change." (Mary Shelly, Frankenstein). AI is certainly a great and sudden change in the IT world, but perhaps not as frightening as Frankenstein. Change is at the core of what business analysts do, and change in the AI field is more prevalent today than ever. So, what type of impact does this change have on the role of the business analyst in AI?

Interactive Voice Response (IVR)
AI adoption is on the increase in businesses, and IVR is an area where there is large demand for business analysts. As businesses increase economies of scale and expand collaboration, there will be a stronger focus on AI tools, practices and procedures, at the centre of which will be people and data. This is where BAs will thrive on a grand scale within AI.

For example, an IVR Business Analyst might work directly with call centre leadership, telephony support teams, or network with vendors to determine business solutions for the IVR applications. AI could report on IVR retention and success levels, and fine tune speech recognition analysis in applications like Nuance Application Report (NAR) or IBM Watson. The BA would be responsible to manage the requirements needed to be programmed into the IVR system. And, the BA would be able to interpret and articulate that output data for management and C-Suite executives, to enable them to make informed strategic business decisions.

An IVR BA could also make recommendations on speech and touch-tone user interface design enhancements, and focus on managing risk within IVR systems by liaising with legal, audit, and risk and compliance teams. This involves effective communication skills, a key ingredient for all BAs. As a conduit between business customers and the technical teams, an IVR BA would still have to identify issues or gaps where crucial technical and business solutions need to be made.  

Radio-Frequency Identification (RFID)
RFID is a form of automatic identification and data capture (AIDC). RFID technology uses electromagnetic signatures with radio frequencies to capture data. For example, using tags RFID can track inventory goods like automobiles during assembly line production, or for pharmaceuticals in warehouses. And, it can be implanted in animals as a microchip to track livestock or pets. RFID tags can also be attached to money, clothing, various possessions, and even people. All the data collected from these tags need to be interpreted by BAs, to determine and understand product trends within the market place. RFID has been projected to grow to $15 billion USD within 2021.  This is definitely an expanding area where BAs in the AI field are in much demand.

Brand Marketing
Noticing and understanding marketing trends are paramount for many businesses, and is a task within the AI sphere where BAs are much needed. For instance, social media campaigns are heavily influenced by the data gathered from TagBoard, which collects hashtag information from social media, or from OneQube, which is an audience development platform. Business Analysts would manage these tools, which track online conversations that focus on detecting keyword usage associated with branding. Of course, this inevitably influences target advertising and marketing use cases via AI.

Crunching and calculating all this data would be done by AI software, while the BA would be better suited to interpreting the analytical data. The results from data queries and reports can be used to understand customer patterns of behaviour, which enables businesses to personalize products based on geographic location, income, age, gender, and a myriad of other categories. Segmenting customer characteristics is at the core of AI. Undoubtedly the outcomes from predictive analytics can heavily impact customer purchasing decisions, allowing more streamlined access to new markets or to new products, delivering products faster to market with greater value, being first to market, or forging new business ventures.

Whether in banking, manufacturing, retail, tourism, and the like, a BA can use data points, produced through AI, to discover what motivates a customer to access a business, and what converts that movement into sales. The objective is influencing buyer behaviour, improving quality assurance, and increasing competitive advantage. 

GPS
I once rented a minivan for a return road trip from Phoenix, Arizona to Southern Utah. It turns out these minivans are equipped with GPS technology. Imagine the hundreds of rental minivans and rental cars all over the world that are being tracked by GPS technology. All this data is collected, managed and analyzed by AI software. BAs are needed to interpret this data to maintain quality customer service: to predict when vehicle maintenance is required; to locate customers during an emergency; to learn how to market a wider range of customers, and so on.

Conclusion
Whether it be IVR, RFID, brand marketing, or GPS, BAs can work within different contexts using a variety of tools from root cause analysis to decision modelling, to determine the performance levels of organizations. 

The BA can look at the holistic picture, and with the assistance of AI, can break down large projects into smaller manageable bite-sized chunks, devote more focus on the crucial people aspect of the business, and contribute to interpreting deeper insights into rich data. These aspects are instrumental in exploiting services and increasing ROI for businesses.

By leveraging AI, a BA’s role within an organization can ultimately be enhanced by effectively adapting to change, no matter how great, and devoting more time to contribute to critical business decisions. Such decisions could include forecasting market trends, providing different perspectives on a problem, facilitating workshops, collaborating with key stakeholders, enhancing current capabilities, understanding customer environments, or promoting an AI strategy, all of which add immense value to a business.

Some fear the role of the Project Manager may be eliminated as the use of Artificial Intelligence (AI) becomes more prevalent in the workplace. Others see the evolution of AI as creating new opportunities, allowing the Project Manager to transform their role to focus on more critical and crucial responsibilities.

Is "AI" just a new buzzword of the week? To some it may be so. Or when you hear "AI" do you envision the Terminator or iRobot. Or do you think of half human half machine like RoboCop, or Bionic Man? These overly intelligent machines are as mythical as the cyclops or leprechauns. Hollywood movies have certainly added to the myth of the super machine thinking and acting like a human, replete with human emotions; conscious, forgiving, understanding, and filled with empathy. Well, that's the world of make believe. The real world is far from this scenario, and probably will not exist within our lifetime.

AI in the business world is something more tame, and less threatening. It refers more to robotic functions such as operations, data collection, tracking and reporting; those repetitive tasks which hold far less value, but which need to be accomplished within business. In complex projects AI tasks save time and improve data accuracy, thus allowing PMs better interpretation of the data. Automating workflows, predicting risks, eliminating human bias, preventing cost overruns, or digging deeper into big data for real-time insights, these are all tasks which allow the PM to spend more time on the human side of a project: the business, stakeholders and customers. AI allows the PM to provide more succinct strategic advice to the business, to be a more substantial leader providing value outcomes, rather than simply being a manager. AI can more effectively guide PMs on where to focus their efforts, thereby more accurately increasing the potential for project success.

AI is not a threat to project management jobs, but a way to spend less time managing and more time doing those tasks that add true value to a business. Project Manager's soft skills like communication, critical thinking, emotional intelligence, leadership and understanding the needs of stakeholders, are more valuable and more marketable than ever, and very much in demand in the world of AI; skills currently void within any robotic AI machine. 

Since the core of the project management profession is not easily transferrable to a machine, PMs should not be fearful of AI inadvertently hijacking their jobs. PM jobs differ widely in complexity, and encompass unforeseeable or taxing challenges which can not easily be tackled by AI. This is AI's limitation. It is relegated to recognizing patterns within data and making conclusions or forecasts based on those patterns. Therefore, AI is optimal for repetitive, predictive or computational tasks. In other words, AI is more like a tool to enhance the project management field, rather than to displace it. Imagination and adaptability is far more fluid within a Project Manager than within AI machines. If anything, the adoption of AI in projects will encourage the PM to embrace techniques which will sharpen our soft skills, making us even more marketable.

The introduction of automation during the industrial revolution in the 18th and 19th centuries gave way to faster manufacturing processes. This was enough to frighten many trades people during that period, who felt their jobs would be lost to machines. The automobile modified transportation, making the use of horses rather obsolete. The introduction of email forever changed the demand for posting letters in the mail. Each one of these transitions involved some form of mechanization, which altered the demands for certain jobs. Rightfully so, AI is yet another stage in this move toward more encompassed automation within the workforce. Like in the past, each time there was a dramatic shift in mechanization, new jobs were created, and many current jobs were enhanced, making them even more in demand. But, throughout this change there was always someone needed to plan, manage, monitor and control the work, and make crucial decisions on the job. The role of the Project Manager will continue to evolve, and will undoubtedly play a pertinent and pivotal role in the world of AI, just as it has done throughout the history of automation.