NSU Technologies provides a variety of consultative services grouped into 3 major categories. Choose one of the services we offer below to read more details about this service.
Our IT Governance practice is built on 37 years of expertise and consists of 7 service concentration areas.
Talent Management – Strategies and processes to develop global talent pools, roles and responsibilities, performance appraisals, retention, and development.
IT Strategy – The development of strategic plans & roadmaps to match the culture and cadence of the business. Understanding, leveraging, and applying the trends in your business, the technology industry, and your business industry to develop concise and impactful plans that will drive results.
Risk Management – Development of an IT Risk Management plan that balances threats, vulnerabilities, and asset value to focus attention on the highest priorities within the IT group. Blending of the IT Risk Management plan with the corporate Enterprise Risk Management Plan to ensure key controls to manage compliance initiatives such as Sarbanes Oxley and PCI-DSS are appropriately managed.
Demand & Capacity Management – Best practices for building processes and mechanisms to manage the inflow of demand into the IT organization, manage resources (internal & external), plan, estimate, prioritize, and commit to IT efforts (programs & projects).
Program & Project Management – Structure, development, and implementation of an IT Program and Project Management function and associatedprocesses and controls.
Value Delivery – Processes to capture and measure value delivered from IT programs and projects to the business. This includes the development and measurement of business cases, post implementation audits, and project scorecards.
Performance Management – Processes and tools to measure the performance of the IT organization. Includes the establishment of organization goals, alignment of goals to company goals and culture, development of IT portfolios (Application, Infrastructure, Process, Talent, Program/Projects), capturing of performance data, building of reporting and dashboards, and communication strategy.
Our Retail Technologies practice is built on 25 years of deep retail knowledge and contains 4 concentration areas that cover the full breadth of retail applications and processes.
Retail Planning – management of the retail product lifecycle from ideation and design through product exit strategies. This includes the development of critical plans to define “what” to sell, “when” to sell it, “where” to sell it, and “who” to sell it to.
Supply Chain – planning and execution of product sourcing, development and movement from supplier to a retail store. This includes managing the transport of goods, warehouse management, third party logistics (3PL), import & flow planning, and inventory replenishment.
Retail Operations – all of the activities needed to establish and operate a retail location including store point of sale, store inventory management, credit and promotions, workforce (labor) management, loss prevention, store audit, customer service, and returns. Retail Operations also encompasses e-commerce and omni-channel functions including customer loyalty, in-store beacons, buy online pick up in store (BOPIS), buy online ship to store, buy online return in store (BORIS), and online ship from store.
Back Office – all of the functions needed to support the backbone of the retail organization including finance, human resources, risk management and compliance, legal, real estate, privacy, and procurement.
Our BI and Big Data Analytics practice is built on over 27 years of expertise in the development and operation of complex analytic-based solutions. This practice contains 3 concentration areas.
Artificial Intelligence (AI) – complex and comprehensive algorithms that simulate human intelligence. This includes a broad set of algorithms such as machine learning (ML) and cognitive computing that allow computers to exhibits traits associated with a human mind such as learning and problem-solving.
Business Intelligence (BI) & Advanced Analytics – business intelligence involves the the evaluation, selection, negotiation, and deployment of leading business intelligence solutions at scale. In addition, defining the standards, tools, and processes to build and deploy enterprise class reporting and dashboards to provide business critical information to business users. Combining BI tools with advanced analytic methods such as predictive modeling, data mining, and big data broadens insights allowing businesses to be more responsive to changing customer demands.
Big Data – the foundation for analytics and artificial intelligence is data. Increasingly data needed for complex analytics such as AI and ML is much larger in terms of size and complexity. The processes and tools to build and maintain these large data stores are critical to the success of any analytics effort. Big data deals with all forms of large, intricate data including structured and unstructured data.
Specialized forms of databases have emerged from the big data space that deal with specific, complex data forms. Included in this are relational, object-oriented, NoSQL, document stores, graph, and in-memory.