If everyone can keep everyone else honest, it will tremendously reduce the amount of efforts for creating false perceptions and damages for mistrust or misguiding in corporate environments. A machine can be maintained to be less political and dishonest than a typical manager/employee and with the automated behavioral statistics collection built-in, it can learn to keep clients, suppliers, colleagues, service providers honest and at the same time give them the suitable room for being self-proactive as humans.
For machine learning to be effective and analysis to be comprehensive, enterprises must have suitable training data. A machine learning algorithm is only as good as the data used to train it. Although there is an abundance of enterprise data, much of it is still not easy to find or use. This type of data is called dark data.
8Manage captures micro behavioral data and produces useful behavioral statistics for both human and machine-learning consumptions.
Program & project management is the nucleus of modern work management. Many projects and programs are out of control because their higher level data don’t link to their fine gain elements and consequently they can be easily fake.
8Manage has built-in fine grain data capture for the following elements in projects and programs to feed machine learning:
Extended Data Capture
The success or failure of a project can be heavily affected by its external parties such as sponsors, user groups and vendors as well as its pre-activities such as project request, feasibility and prioritization.
8Manage allows the project platform to be extended to include different kinds of stakeholders and different pre-project activities so that it can capture micro behavioral data of all parties before and after a project is initiated.
Resource Allocation
Since the schedule change of one project can affect its resource allocations and also resource allocations of other projects that it shares resources with, resource allocations need to be redone frequently. It is also beyond the average human’s capability of seeing through all impacts each time.
8Manage can capture the resource allocation data so that a learning machine can learn the skills, progressions, achievements, mobility and preferences of individuals and combine with availability , dependence, risk and cost information to provide advice on or automatically perform resource allocation for activities and projects.
Success Factors
8Manage can automatically detect the positive stakeholders’ behaviors such as user involvement, executive support, clear requirements, proper planning and realistic expectations and negative stakeholders’ behaviors such as incomplete requirements, changing requirements, lack of resources and technical incompetence and generate data for machine learning.
8Manage can automatically capture the behaviors of sales teams, buyers and delivery teams in pre-sales, sales and post-sales activities. A learning system can learn from the behavioral patterns to possibly perform target discovery, personalized marketing, opportunity scoring, service forecast, account and account management
Target Discovery, Personalized Marketing and Opportunity Scoring
By learning from the behavioral data, a learning system can identify interest patterns and discover marketing targets and make recommendations for SEO, SEM and personalized marketing. A learning system can also learn from client and market data and automatically match the products, services, omnichannel, sales reps, messages and timing for marketing actions and track responses, detect interest level and obstacles and recommend further marketing actions.
Account Management
A learning system can learn from the internal presale, sales and post-sale behavioral data as well as external big data and can alert the account managers, delivery managers and/or service reps to take actions at the appropriate time via the omnichannel. When the learning system detects low customer satisfaction, it can automatically diagnose the problems and suggest corrective actions.
By learning from the behavioral data, a learning system can also proactively seek any new sale (including up and cross selling) and repeated sale opportunities and referrals and automatically alert the sales reps for actions. A learning system can also learn from the behavioral data to forecast client loyalty.
A learning system can learn from 8Manage’s customer request and complaint data and product service patterns to forecast product problems and service and resource needs and recommend the types of services and service token quantities to propose to different clients.
Service Intelligent Process Automation
By learning from the service data, a learning system can automatically match the service pattern of the current call to the previous calls with similar patterns and provide statistical information on severity, urgency, effort and time-to-resolution to the service rep. A learning system can also learn from product data and service patterns to recommend diagnostic questions to ask to help the service rep to analyze the issues.
Resource Forecast & Performance Prediction
A learning system can learn from the service data and detect insufficient service resources (including service personnel and spare parts) for different types of services and provide input for staff acquisitions, outsourcing forecasts, training plans and replenishments.
A learning system can also learn from the service personnel performance data and service patterns to predict service performance and client satisfaction and recommend actions to improve performance and client satisfaction.
8Manage can automatically capture the behaviors of requestors, procurers, controllers and suppliers for the following activities:
Based on the procurement behavioral data that 8Manage provides, a learning system can learn from each procurer’s patterns and determine which procurer is the best for which types of product and service acquisitions to advise the procurement managers what procurers to utilize under what situation to yield the best results. Similarly, a learning system can learn from each supplier’s patterns and advise the procurer which supplier is the best for which types of product and services with which procurement and delivery methods in what regions to advise the procurer what to use to yield the best results.