273 Decision Making courses in Uckfield delivered Live Online

The need for key staff to have commercial skills is paramount, as the public sector is increasingly opened up as a commercial market, in which organisations compete against each other and the private sector for contracts. Generating additional income and being commercially aware is vital for this to be a success, and is what many public sector organisations are looking to do. This programme will help you: See commercial awareness as not just another skill-set, but as a different mind-set Use a variety of tried-and-tested commercial, analytical decision-making techniques and tools Define your commercial objectives Develop a strategic focus Start looking at service clients as market segments Analyse, in a competitive context, your service offering Plan a commercial strategy, prepare for its implementation and see it through to execution 1 What is commercial thinking? Understand what it means to be a commercial thinker Identifying commercial opportunities often involves not only a different skill set but also a different mindset; looking at the services that you provide 2 Defining strategic commercial objectives Defining your key commercial objectives Prioritising your strategic objectives Two key strategic planning tools:Resource and Competency MatrixPESTLE How to apply these tools to your particular situation 3 Developing a strategic focus Decision-making on how to compete in the markets identified by your strategic objectives requires a strategic focus Developing strategic focus A tool for helping you to make those decisions: using the Ansoff Matrix 4 Defining customer targets How to think more commercially by understanding who all your customers are and how they differ from each other how to apply the principles to your areas to identify the type of customers you have and their key characteristics - Customer segmentation Who are your customers? How do their needs vary? - Scenarios 5 The competitive market place Understanding the competitive forces at play Different types of competition Analysing your competitive environment using Porter's 5 Forces model 6 Meeting stakeholder expectations Two simple models to help you identify the key stakeholders who could influence your commercial environment How to use your stakeholders to help you achieve your commercial objectives 7 Implementation - systems, structures and processes Effective commercial activity involves working with others to implement ideas and strategies What do you need to have in place before you implement your commercial strategy? How to health-check your organisation prior to implementation using the McKinsey 7S framework 8 Implementation - people and culture A good commercial strategy only works if the people involved buy in to the ideas and if the culture of the organisation is conducive to the effective implementation How the latest thinking in behavioural economics can help you develop your culture and people to work commercially 9 Tools and checklists Be more commercial within your sphere of influence using a commercial checklist to help you Using the checklist as a benchmark against the most commercially aware organisations Using the checklist as a health check - both corporately and individually

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Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

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SAP CRM Training Online SAP CRM (Customer Relationship Management) module empowers you to manage all of your customer-related data and contacts. In SAP CRM training course you will learn how to leverage functionality for the full spectrum of CRM processes including sales, service, marketing, and operations. Powered with an understanding and knowledge of the comprehensive functionality in SAP CRM, you can easily manage the entire customer life cycle efficiently and intelligently. SAP CRM is one of the significant part of SAP Business Suite to manage customer relationship. It supports all customer-focused business areas such as marketing, sales and service. A component of SAP CRM, CRM Analytics, enables organizations to gather all relevant information about various key factors such as a customer and analyse the knowledge base to incorporate insights into operational processes and helps in strategic decision-making. SAP CRM Basic Functions and Master Data SAP CRM Sales, Marketing, Services and Middleware SAP CRM WORKSHOP/Project orientation Training

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A key-worker role is to provide the best individual care for people they support and carry out effective assessment and support planning. Staff need to know how to motivate individuals to achieve their personal goals and understand how to advocate on their behalf. Staff also need to know how to improve communication between colleagues, individuals, other professionals, and contribute to service improvement.