Sierra Digital
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Business Analytics Consulting

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Sierra™ Digital Inc sees business analytics is a process of methodical exploration of business data with emphasis on process driven analysis. Our service is used by clients committed to data-driven decision making. Our business predictive analytics is used to gain insights that inform decisions and can be used to automate and optimize business processes. Data-driven enterprise treat their data as a corporate asset and leverage it for competitive advantage. Our BA depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making.

Sierra™ Digital Inc recognizes the growing popularity of business analytics. More recently, data warehouse appliance have started to embed BA functionality within the appliance. We work with major enterprise system vendors who are also embedding analytics, and the trend towards putting more analytics into memory is expected to shorten the time between a business event and decision/response.

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Our Understanding on Business Predictive Analytics Maturity

Business Analytics Maturity

Our Business Analytics Approach – Sample Approach

Business Analytics Approach

Our Differentiators

  • We have readily deployable hosted solutions
  • Using combination of SAP’s best practices and our proven methodology to accelerate implementation, low risk and cost.
  • Business can realize their future state from day one
  • Reference architecture
  • Predefined data model, views, and functions
  • Easy to customize and adopt business changes
  • Support for future software upgrades/patches
  • Flexible deployment plan and rollout strategy
  • Wide range of engagements within SAP and the SAP ecosystem to keep abreast of latest tools and technologies

We differentiate our business analytics implementation by integrating corporate strategic objectives to analytics.

business analytics implementation

Our Use Cases

We have several industry use cases, and we will be employing our use cases during several stages of business analytics implementation such as planning requirements, design, build and testing & deployment.

Health Care
Our Predictive Analytics Use Cases
  • Claims fraud detection
  • Demand driven forecasting Employee attrition & profitability
  • Employee recruitment & talent management
  • Inventory level forecasting & management
  • Quality improvement (six sigma efforts)
  • Workforce planning & management
  • Sales forecasting
  • Supplier performance management
  • Logistics management
  • Healthcare expenditure control
Our Predictive Analytics Use Cases
  • Product purchase affinity, within a single or across time for a given customer
  • Up/Cross sell recommendations based on historical product purchase affinity and customer attributes
  • Bundling recommendations based on product purchase affinity history, and sample revenue/ margin goals
    • Increase sales of long tail product
    • Increase deal margin on a high volume low margin product
    • Combine products and services
  • Segmentation and clustering customers, including Regency, Frequency and Monetization
  • Projection of customer life time value based on order history
  • Identify customer at a risk of leaving, based on regression order analysis and interaction history

Our Business Analytics Reference Architecture – Sample

Business Analytics Reference Architecture

Sierra™ Digital Inc Leading Practice

  • Reduce total cost of ownership , leverage existing investments and assets and build long-term solutions.
  • When a client wanted to implement BI 4.0 solutions on a SAP and NON SAP transactional system landscape with a retention of existing data warehousing assets. As a leading practice , we usually approach this type situation by implementing a long term centralized enterprise data warehousing (EDW) solutions followed by a multi-source universe to take an advantage of the existing data warehousing assets. The multi-source universe will provide business semantic view to the end-users and hide the technical complexity
  • We bring different source systems data into EDW by using BI 4.0 data services , this approach will enable consistency and long term stability in effective data integration , data quality , data governance and data management across business process

Sierra™ Digital Inc  Accelerators

  • Standards and Guidelines for Multisource Universe design
  • Industry Specific KPI and Information Modeling for Data Integration and Universe Design
  • Pre Build Universe content to learn and develop universes for a business function
  • Educational content to learn and understand multi source data access
  • Framework for Data Access from multiple sources
  • Our Implementation Expertise

Ensure immaculate business process management with our consummate team. Contact to collaborate with us!

Topics – Data & Analytics

Client Challenges
  • Experienced planning and forecasting processes that were inconsistently distributed, manually intensive, and costly across the company’s geographies, segments, and divisions; limited additional insights into numbers (ex. no scenario capabilities)
  • Faced significant challenges in the current planning and forecasting environment globally due to the lack of centralized automation
  • Lacked scalable country-specific non-integrated systems and required significant effort to ensure better data quality; disjointed data structures and hierarchies were time and effort intensive
  • Looked to deploy more globally-consistent IT tools to enable increased automation, improve data quality, reduce cycle times, and standardize processes thus allowing more time for value added activities
  • Looked to Sierra initially to help support the vendor selection/technical due diligence process, which resulted in BPC being the most appropriate solution
Sierra Approach
  • Used BPC to establish global standards (IT and process) with the ability to adjust the following based on local needs:
    • Global Alignment: The global finance operating model requires more globally consistent IT tools to enable increased automation, improve data quality, reduce cycle times, and standardize processes thus allowing more time for value added activities.
    • Local Implementation: Require local implementations that fit into the global standards, but allow for unique localization needs. North America Commercial (NAC) was selected as the first local implementation due to its high-level engagement, knowledge, and well-defined business requirements.
  • Assisted in the development of the SAP BPC proof of concept to ensure a technical fit and the key to stakeholder buy-in
  • Conducted a fit/gap analysis of the client’s global functional requirements with SAP BPC to validate a good fit
  • Worked with project leadership in developing the project business case and Currently assisting the project leadership through the global and local project approval phases
  • Conducted global work sessions to develop a representative set of planning and forecasting requirements for the enterprise
  • Gathered detailed business requirements and Implemented global process design of the planning and forecasting processes
  • Oversaw SAP BPC functional design; validation and quality oversight through SAP BPC technical design, configuration/development phases and Provided testing assistance and support
  • Provided overall program management through BPC implementation
Business Benefits
  • Implemented global standard processes and procedures that will utilize a single technology platform with a centralized governance model
  • Implemented a global technology footprint that will support the global integration of the planning and forecasting landscape across the client organization to:
    • Standardize data definitions, hierarchies, and dimensions to minimize reconciliation and consolidation efforts
    • Enable rollup of local planning models to the group level planning and vice versa (target setting)
    • Automate algorithms to support corporate, group, and local allocation needs and Implement system-based controls and approval workflows
  • Decreased the complexity and operational cost of their current tool set
  • Improved automation and thus increase efficiency in PPM staff workload and Standardized processes and reporting to enhance financial decision making
  • Enabled scenario planning and rolling forecast capability and Improved and increased time for analytics and insight development at multiple levels

Our Healthcare Business Analytics – Sample