As we look into the future and impact of the re/evolution of technology on society, it is quite clear that impacts have been dramatic in certain areas and not so much in others. For example, mobility and technology has unleashed digital capabilities in 3rd world rural economies unthinkable a few years ago. Geotagging, satellite data, and drone technology are being used to verify crop-cutting experiments and improve intelligence on farming areas. Similarly, there is rapid growth of mobile payments in India (Paytm) and Africa. On the other hand, we still find basic inefficiencies and gaps between interfacing systems. workflow, and humans. The purpose of this article is to explore some simple ideas and examples of how impactful solutions may be designed and implemented for orders of magnitude improvements in business and consumer environments.
Example 1: Current job seeking and candidate evaluation systems are heavily flawed. It is a case of a mass production line producing defects at incredible high rates. Would any production organization allow such waste to go unchecked? No. If we consider the current job boards and employer-candidate matching portals, it is clear that their effectiveness to actually match good candidates with roles is very poor. I have no statistics to prove it, but is based on my personal experience and reading. All HR systems use keyword matching to match resumes to job descriptions. Since they look for exact matches, unless the resume matches the job description exactly for a keyword, a very good candidate’s resume will not clear the filter. This is due to the complete lack of context search abilities in today’s HR technology. Thus, the phrase “requires project management” will miss a resume stating “project managed 5 large projects”. Unless HR systems figure out a way to evolve the technology to match context to candidate, many fabulous candidates are being missed. It is a tremendous loss for organizations and the candidates. Not only that, these systems are often used to post false, out-of-date and already filled, or EEOC satisfying openings. Technology providers should focus on this capability now if HR processes are to improve from this aspect. This will also help candidates who view today’s job market scouring using the internet as a hopeless waste of time.
Example 2: Use of large-scale analytics and process observations for business problem solving. The trend is for big data from many process outputs be analyzed for proactive business decision making. Currently, it requires integrations of different data systems or manual interactions with data and reports to compile the information. Business process data is mostly from transactions and near real-time: production line throughput, claims processing, payment processing, others. Near real-time business process output analysis with business rules or environmental conditions will directly enable and produce better business actions. For example, if bad parts are being produced which variables can be adjusted and effect observed in real time?; or, from claims processing it is possible to design interventions and offer care management for population health improvements.
The proper execution of the ideas will require development and implementation of integrated systems using big data, process analysis, AI and context searching, and well-designed and integrated systems. While this is not easy or simple, it is highly achievable in today’s technology environment.