Informed Business Decisions from accurate data
In order to ensure the success of your Analytics project, we work very closely with our clients on initial strategy and envisioning.
We follow our proven methodology, which helps us define and envision the final solution – and more importantly define how the analytical capability can be used across the company to improve business performance.
We do this by using predictive analytics to foresee issues and opportunities before they actually occur. At this preliminary stage, we work closely with you to define high level architectural objectives, execution timelines, and help with estimating the budget for the overall programme.
The objective of the planning stage is to clearly define the overall project in detail. This includes defining the goals and objectives, scope and deliverables, plus the risks and constraints.
Particularly important during this phase is stakeholder management, which ensures that the overall objectives of the business end users are met and aligned to the business objectives of the organization as a whole.
We use a number of techniques such as prototyping, to ensure that the final deliverable is clearly defined and aligned with the expectations of the end users.
Implementing a Business Intelligence/Analytics project typically involves considerable investments in terms of time and money.
Our delivery methodology is designed to ensure that the final product is of the highest quality, and delivered on time and within budget, while also being adopted well within your organization.
All of our projects are delivered using fast release cycles, so that you can get your analytics enabled in weeks rather than months.
Enabling Analytical capabilities for our clients is not about technology choices. We have experience with various tools and technologies to help our clients meet their needs. List below outlines our high level capabilities from the technology angle:
Data management and backend
Databases and Source Systems Connectors: SQL Server, Oracle, DB2, Oracle E-Business Suite, SAP, Dynamics CRM, Dynamic AX.
We can extract information from a variety of source systems and databases. In the case of ERPs and industry standard systems, we utilize our own (as well 3rd party) connectors, which are aware of underlying database models and allow us to extract the right data at a rapid pace.
ETL: SQL Server SSIS
We leverage standard ETL tools to extract the data from your source systems, and help you effectively manage the dataflow.
Modern Data Warehouse, OLAP and In-Memory Models, Semantic Layer: SQL Server, APS (Appliance)
The majority of our enterprise implementations involve designing and building a data warehouse. Today’s landscape of tools and technologies allow you to combine, aggregate, and access your data in many complex ways. We help our clients make the right decisions around these key architectural choices.
Data Warehouse Automation: TimeXtender, Wherescape
By leveraging data warehouse automation, we help you accelerate and automate your data warehouse development cycles, while assuring the highest quality and consistency. This helps us deliver an automation of the entire lifecycle of your data warehouse; from source system analysis, to testing and documentation, which leads to faster and more consistent implementations.
Big Data Infrastructure: Hadoop, HD Insights (Azure Cloud), IOT Hub, Cloudera, APS (Appliance)
In order to manage and gain insights from all the structured and unstructured data within your organization, you need a solid platform that is capable of handling of data of various volumes, size and velocity. We work with data warehouse and big data solutions from quality providers such as Microsoft, to provide a trusted infrastructure that can handle all types of data, scale to any level required, and do so with real-time performance.
Master Data Management: Informatica
Master data management (MDM) is a methodology that identifies the most critical information within your organization, and creates a single source of its “truth”. This process involves number of technology components that manages data integration and data quality, however the end result is a much simplified architecture.
Deployment Options: On Premise, Cloud, Hybrid
We help you make decisions about the deployment choices for your analytics solutions. Our first choice is always cloud-based, as it brings many advantages in terms of manageability, cost, and scale. If the cloud is not an option for you for any reason, we can design a traditional in-house or hybrid architecture.
End User Tools and Data Visualizations
They say “a picture speaks a thousand words”, and good data visualization gives you exactly that difference.
Data not only needs to be accurate, but also presented in a meaningful and useful way. Reports, dashboards and mobile interfaces need to be designed with these usability principles in mind. We ensure that you and your users will fully understand the insights gained from your analytics data.
Although we are technology-agnostic when it comes to your choice of front-end, our expertise and strengths are with the toolsets listed below:
o Power BI
o Pyramid Analytics
o SQL Server: SSRS
o Cortana Intelligence Suite
Becoming a modern data-driven organization takes time, and we are always excited to help our clients climb the ladder.
This journey always starts with the ability to accurately work with historical data, and then gradually move towards the ability to predict future events and spot trends.
We use tools such as Azure Cortana Analytics Suite and Azure Machine Learning, while using custom algorithms to help you accomplish various complex data-driven tasks. For example: customer churn prediction, revenue and demand forecasting, customer segmentation and much more.
o Azure ML Algorithms
o Model Development
Analytical projects offer tremendous benefits, however it can also be a challenge to get people to use the system to its full potential.
This is why we include an adoption roadmap, to ensure that not only has the technology been delivered and working, but that it is also actively being used. This is not just about training users, but an end-to-end process that starts during the design and planning stages of the project, along with capturing the objectives of internal stakeholders.
The insurance industry has been going through a rapid digital transformation over the last few decades. Many insurers and insurance brokers are realizing that traditional insurance products have become a commodity, and very often customers make decision based entirely on cost. Due to the complexity of the distribution model, carriers and brokers see their operational costs rising while having significant pressures on their margins and commissions.
The lack of good business analytics, including a holistic view of business data, is a significant challenge for many players in the industry. This is especially true when competing with digital first players that have built their business model around “technology first” propositions. They can offer consistently lower insurance premiums, while maintaining or growing their profit margins.
We work with insurers and insurance brokers, and have vast experience in this industry, with a particular focus on the various risk lines. We help insurers and brokers overcome the challenges of today’s competitive business environment, by providing them with the insights needed to lower their operational expenses, attract new customers, as well upselling new products to the existing customers base. Many of our clients have gained a much-needed competitive edge by understanding and analysing their data.
Basic Analytics and Pre-configured KPIs
- Operational Excellence (Fulfilment, Turn Around Times)
- Customer Segmentation
- Customer Demographics Analysis
- Claims Analysis
- Risk Lines
- Life and Critical Illness
- Property and Casualty
- Next Best Action
- Advanced Forecasting
- Claims Fraud Detection
- Customer Churn Predication
- Cross Sell Optimisation
Retail & Consumer Goods
Traditional Retail and Consumer Goods merchants are facing real challenges related to the availability of real-time data, in order to make informed decisions about their business at the right time. Not having critical information readily available, makes it difficult to compete with pure e-commerce players – who have built their business propositions on fully digital systems with near real-time access to information.
Retailers often capture large volumes of business data, which can be used to effectively understand the performance of their businesses. Many also use advanced analytics and models to uncover insights which can help them compete.
Our Teambase Analytics for Retail offering is a set of industry standard KPIs, dashboards and analytical models, which help us rollout various basic and advanced analytical capabilities. This is irrespective of the underlying data sources (e.g. ERP, CRM, POS). The product covers various retail sub-categories such as grocery, fashion, healthcare, leisure and entertainment, leasing retail and more.
Basic Analytics and Pre-configured KPIs
- Store Loss Prevention
- Customer Loyalty
- Market Basket Analysis
- Advanced Forecasting
- Fraud Detection
- Inventory Optimization
- Customer behavior patterns
- Product Price Point Analysis and Optimization
Media & Entertainment
One of the key challenges for Media and Entertainment organizations today, is to effectively and accurately measure its audience, in order to understand their experiences and interactions with various media channels.Understanding the customer is key to delivering relevant and timely content, which is directly correlated to increasing revenues from content consumers and advertisers.
Teambase Media and Entertainment Audience Analytics provide Media Networks with insights to content performance and audience affinity.
Understanding your data further can help increase advertising revenue potential, and optimize channel marketing budgets. The ability to manage and predict content ratings can optimize matching program content to advertiser needs.
The solution also has the ability to pull information from multiple sources, covering program ratings, audience demographics, and market detail. The historical ratings data is used to feed an analytic model that predicts potential content ratings.
- A full Media and Entertainment data model with over 30 visualisation components
- Over 50 metrics to analyse
- Analyse audience trends and defend a channel’s leadership position
- Understand competitor program ratings to see movement in Share of Audience and TRPs
- Predict program ratings and optimize ad spot selling to advertisers.
- IPSOS data analysis
The construction industry is responsible for undertaking some of the most expensive and complex projects in the world. It can be a huge challenge to find a balance between architects who strive for innovation and creativity, engineers who want to keep quality while delivering on time, and owners who want to contain the project costs.
Managing construction projects is a difficult task, with many factors contributing to a high risk of failure. Teambase Construction Analytics provides a balanced and analytical perspective across both the Commercial and Project Progress aspects of a project. It leverages multiple sources of data, to distil down the most important metrics while taking out the “guess work” from managing risk on the project.
- Full data model with Commercial and Project Progress metrics
- Executive view across all projects
- Analyse Project Profitability forecasts in context of Actual and Planned Work completed
- Analyse Cashflow and Certified work completed along with Sub-contractor payment summaries
- Optimise Manpower planning forecasts
- Milestone analysis surface the most important milestones for monitoring
- Over 200 metrics to work with across Planning, Engineering, Procurement, Construction and most importantly Finance
- Set targets for KPIs that matter
- Based on Microsoft SQL Server Enterprise
- Leverage all the goodness of Power BI to share the data model and visualisation in a governed fashion across the organisation