Essentially every business today is at some stage of digitalization, striving to increase their workforce's efficiency and productivity.
However, as markets evolve, efficiency alone will not keep businesses thriving. By providing context-relevant information, predictive insights and constant learning at every point of work, businesses can increase proficiency in real time, throughout the enterprise and beyond.
Proficiency will become the essential competitive attribute, the hallmark of agile businesses.
Dynamic Skills Needed
Knowledge ages rapidly in the digital workplace. Yet organizational training programs can be expensive, disruptive and often times unhelpful as they train people “just in case” they might need the information or skill in the future. Organizations find themselves further constrained by an inability to find people with the right skills to hire and hence try to rapidly increase proficiency throughout the organization.
Intelligent workplaces use their technology infrastructure to put knowledge of the enterprise (and beyond) at the fingertips of everyone in it, in the context of their individual tasks and roles.
These organizations become responsive to every question, proactively recommending relevant content and people who can help, and suggesting what matters most to individuals in every context. This allows workers to get the job done more effectively, make better decisions and gain skills through constant, real-time learning.
The infrastructure relies on a combination of search technology, unified, encrypted indexing, secure connectivity, behavioral analytics and machine learning.
What an Intelligent Workplace Might Look Like
1. Provide Relevant Answers, Securely
As Gartner reports in its brief, Insight Engines' Will Power Enterprise Search That Is Natural, Total and Proactive, successful programs will require “the ability to look across any and all repositories irrespective of what kind of data source it is.”
This is the first tenet of a successful workplace: open all stores of data, securely, because often the most valuable knowledge populates the long tail of data. Indexing must respect the underlying security of each system or organizations will not open their data stores. Cloud indexes provide a fast economical way to “virtually” unify on-premises and cloud-based information.
2. Make it Proactive and Predictive
Once you have a unified index and people using information, use behavioral analytics to understand how people interact with and use information, and the outcomes they achieve with it. In turn, analytics feed the machine learning engine to automate relevance tuning, provide query suggestions, recommend experts who can help, and enrich results with proactive insights.
The combination of analytics and machine learning reduces past reliance on metadata projects and complex classification schemes, making high levels of relevance easily achievable.
3. Integrate with Worker’s Roles
At this point, the platform should be able to suggest content that matters to employees based on their role, profile, current work and the behavior of “others like them.” With UIs embedded where employees work most, it is possible for the intelligent search engine to understand employee's context of the employee and automatically recommend what will help most.
Role-based UIs are key to embedding proactive insights where people work most - in systems of engagement and across all devices. Success is measured in adoption levels (continually growing), click-throughs (increasing) and click ranks (most relevant content is most apparent).
4. Learn From the Digital Crowd
The proliferation of systems and data makes it near impossible for knowledge management to curate all relevant knowledge.
However, following the use of and success with information may become its curation — automatically. Behavioral analytics can identify the information that generated successful outcomes and which did not, in turn boosting the relevance of information used successfully by “people like me” seeking similar outcomes. Analytics can further uncover content holes as well as an individual’s true intent, regardless of the language used in the search.
Today's knowledge workers are willing and able to handle more complex problems on their own when provided with contextual, personalized insights. This is how they prefer to learn and work, and how smart organizations will both help them gain the proficiency they seek and retain a talented, engaged workforce.
Title image Luis Llerena