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Corporate Culture

The most successful of organizations tend to be ones where learning is a continuous and not a one-time process. Such learning organizations see continuous improvement as their hallmark. Small, evolutionary stages are preferred over single-use revolutionary corporate training programmes. This is because now newer strategies become stable or obsolete over shorter durations. The depreciation in employees’ skill sets is taking place at a faster pace. Also, disruptive competitors are often derailing established practices rendering them irrelevant. Even employees themselves have several means of learning and development rather than being solely dependent on the specific training managers. To ensure that continuous learning gets integrated into the sustainability cycle, learning leaders will need to put in place a few recommended procedures. The entire training process will need to get reengineered to the current scenario while individual roles and responsibilities will evolve. Certain managers, executives and supervisors will need to be appraised for their learning leadership roles. Greater bits of technology and social learning will need to be integrated. Greater amount of analytics must be used. Finally, the greatest transformation ought to occur in the mentality to shift away from being the gatekeeper of learning solutions to simply being an enabler.


In spite of the best of efforts, most corporate in the USA have failed at their diversity drives. Some tactics have been identified which can lead to a more diverse workplace. First of all, equal career and growth opportunities must be accorded to all. This includes all management training sessions. A genuine organizational change needs to be brought out through such programmes. Formal equality programmes may be nurtured as done by the New Marketing Institute (NMI). Members from any ethnicity, gender, religion or career background can embrace new skills accordingly. Another method at executing this is by meeting each person individually as McKinsey has instituted. This is particularly important because each individual has different scope or requirement of learning.


Increasingly organizations are targeting a more diverse workplace as it fosters creativity and also allows them to align with the Employee Non-Discrimination Act. Some strategies have been noted, following which companies can rectify their non-diverse workplaces. First of all, for new recruits small teams must be set so that it is easier for them to integrate within the larger organization. Then mentorship must be incorporated to ensure talent management and retention while striving to meet their career objectives. Corporate training programmes must involve learning and development so that relationships many be forged along with skill upgradation. Off-work activities must also be scheduled. Employees must be involved in recruitment as well. Communication patterns must be streamlined is such a way that there is no generation-level discrimination. The company policies must also be drafted in such a way that they are in sync with national or international laws. Annual important events must be celebrated communally. Proper decorum must also be established on ways to address differently-abled or transgendered employees. Beyond that the entire functioning must be set in such a way that physical disabilities do not create any hindrance to career growth.


A study conducted by Forrester Research found out that last year, just over a third of enterprises are using some form of Artificial Intelligence (AI), but that number is expected to grow to over three-fifths of the market by the year 2018. Some of the AI powered technologies have been identified that are currently trending and have the potential to transform the market. One is Natural Language Generation that produces text using computer data so used in customer service and abstracting business intelligence reports. Then there is speech recognition of human voice and dialect whose main vendors are NICE, Nuance and Open Text. Virtual agents are assistants that can network with human beings. Tech leaders such as Apple, Amazon, Google, IBM and Microsoft are presently engaged in this. Then there are Machine Learning platforms such as SAS and Sky tree. There is even hardware that is run using AI. Deep Learning Platforms can be used to crunch business analytics from the vast data that gets stored. It helps in pattern recognition using applications from Fluid AI, Ersatz Labs, Peltarion and others of the ilk. Biometrics have long been in existence but now have wider uses than speech, body language or touch recognition. Robots are also being used to process human functions that are of repetitive nature. There is Natural Language Processing (NLP) that uses machine learning principles through statistical analysis to detect fraud, empower automated assistants and data mining.



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