Building technology companies, Forum

The Next Wave Of IT Innovation – Empowering Broad Based Employee Productivity

Anik Bose and Yashwanth Hemaraj from BGV share their perspective on the next wave of Enterprise IT Innovation. The democratization of knowledge is the acquisition and spread of knowledge amongst all workers, not just a fraction of highly educated workers. The printing press was one of the early steps in that journey. The creation of libraries during the industrial revolution was another, with the Internet raising the sharing of information and knowledge to unprecedented levels. BGV believes that the digital transformation of the enterprise will create a significant wave of innovation around empowering productivity and continuing the process of democratizing knowledge – not only through automation of knowledge workers but also by enabling less skilled workers to do more. The innovation around big data storage and analytics has pushed businesses to adopt data analysis tools to make data driven decisions that lower costs, improve productivity and deliver increased value to customers. Advances in artificial intelligence, machine learning, and natural user interfaces (e.g., voice recognition and semantics analysis) are making it possible to automate many knowledge worker tasks that were long been regarded as impractical for machines to perform. For instance, some computers can answer “unstructured” questions (i.e., those posed in ordinary language, rather than precisely written as software queries), so employees or customers without specialized training can get information on their own. Prescriptive and predictive analytics tools are being used to augment the talents of broader sets of employees as well. In addition, visualization tools are beginning to democratize big data by giving users broader flexibility to analyze data within a self-service business intelligence environment. Allowing users to explore, summarize, and visualize data in the way they see fit enables users with less advanced data skills to gain greater comfort with data and draw increasingly sophisticated insights. We believe this opens up possibilities for far-reaching changes in how work is organized and performed to drive productivity gains. Several underlying technology trends are enabling this emergence of innovation in the areas of advanced analytics and data visualization tools. These include:

  • 100X increase in computing power from IBM’s Deep Blue to Watson
  • Advances in machine learning, AI and natural language interfaces
  • Breakthroughs in new algorithms, data storage principles and new data sources
We believe that empowering “broad based” productivity will become an increasingly important component of any successful startup’s overall value proposition in the future. The economic rationale is simple and compelling – a broader user base will significantly shorten time to value for customers, drive faster adoption and therefore revenue ramp for such startups. Enterprises are facing increased pressure to make data driven decisions in order to remain competitive on one side, and a severe shortage of people with data analysis skills on the other side. This is true across multiple verticals. A research by the McKinsey Global Institute projects that by 2018, the US alone may face a 50% to 60% gap between the requisite demand and supply of deep analytics talent, i.e. people with advanced training in statistics or machine learning. In November 2014, a special Parliamentary Select Committee in the United Kingdom’s House of Lords reported a global shortage of “no less than two million cybersecurity professionals” by the year 2017. This gap is preventing companies from effectively executing their critical business strategies. The presence of such severe talent shortage and high demand also leads to high turnover and hyper wage inflation, further increasing economic pressure on enterprises. A few examples:
  • Cyberflow Analytics ( visualization and network scale behavorial anomaly detection allows IT personnel in the Security Operations Center to deliver automated incident response and remediation without needing to rely purely on highly skilled security analysts who are in short supply. This is an increasingly important value proposition for enterprises as they turn to MSSP’s to manage their security needs
  • Profitect ( offers prescriptive analytics solutions for workers in retail stores aimed at optimizing store level decisions that impact profitability without needing to incur the expenses of a dedicated data science/analyst team
  • Swiftshift ( enables retail and health care enterprises to communicate and optimize scheduling for their shift workers by leveraging a mobile automated workflow management tool thereby improving productivity, minimizing operations disruption from due to absenteeism while reducing agency costs
  • Ayehu ( enables the rapid automation of any IT process workflow, thereby freeing up time to allow IT personnel to improve customer service levels as well as implement complex solutions without having to rely purely on expensive IT resources (e.g. ServiceNow help desk implementations)
We are not advocating that blind automation is the panacea because continuous learning, manual control and governance policies will continue to be a necessary ingredient within any automation framework. In the 1990’s IT tools enabled creative managers to redesign core processes or innovate around products and services in response to changing business conditions. But by far, the narrowly defined IT producing sectors made the most direct contribution to productivity growth – accounting for 8% of GDP in 1993 yet contributing a disproportionate 36% to productivity growth between 1993 and 2000 (Source Mckinsey Global Institute Report 2002 – How IT Enables Growth). over the coming years the impact of IT on productivity will be far more broad-based, with advanced analytics and data visualization cutting across sectors (retail, healthcare, banking, manufacturing, etc…) with mobility and cloud becoming delivery foundations for such applications.