Sagence Group Services

Services that turn information into a highly productive asset

• Analytics
• Information Asset Management
• Applied Decision Science

Organizations are capturing and storing data at an exponential pace. Valuable data (about, for example, customers, product and services, logistics, and price) is estimated to double every 18 months. Regardless of location or format, this data constitutes your firm's information asset.

You can turn this information into a highly productive asset by using a variety of information delivery and data analytic techniques. These capabilities, when properly developed and deployed, will support your strategic priorities and help you measure your success, which will lead to: new insights about your customers, markets, and operations; new decisions; and changes in your operations.

Using your information to drive change relies on two core capabilities: (1) data analytics and (2) information asset management. Together these core capabilities can be a great source of competitive advantage.

Analytics

Many businesses have a long history of investments designed to improve business decision making. Most have contributed to building information assets; however, they have not necessarily delivered improved decisions. That is now changing with the recent trend of investments in business intelligence (BI). These investments are allowing organizations to further deploy and distribute informed decision-making capabilities.

As a powerful component of BI, data analytics takes informed decisions a step further. Building a data analytic capability can be a great source of competitive advantage; it can even drive your firm's strategies, as opposed to just measuring them. We call this a Strategic Information Capability.

Sagence Group has the skills and experience to help you identify and exploit analytic opportunities, and we do it in a pragmatic and collaborative way, so it becomes a sustainable capability for your organization.

The Case for Analytics

Over the past decade, many organizations have invested a significant amount of time and resources into re-architecting their enterprise systems. Whether it’s an ERP system or a CRM package, the main objective is to operate the business more efficiently to improve decision making. While these systems are critical for capturing data, better decision making often requires more. And unfortunately, it is decisions – not data capture – that drive the biggest returns.

The next wave of investment was in data marts and data warehouses. These technologies provide a layer of infrastructure that essentially extracts data from operational systems for the purpose of storage, integration, and delivery. Although the warehousing wave is another great leap toward better decision making, it really just sets the stage for BI.

Usually built on top of data warehouse infrastructure and often enterprise systems as well, BI is all about decision making. It refers to the skills, tools, and technologies that retrieve, analyze, and present organizational information in support of business decision making. BI tools and processes are allowing firms to not only dig deeper into their information asset, but also to distribute decision-making authority much more broadly.

Sagence Group regards data analytics as a powerful component of BI. While much of BI consists of operational dashboards and other reporting elements, data analytics attempts to identify relationships, make inferences, and formulate predictions through a variety of statistical techniques. The insights from data analytics can be very powerful. They can determine and help execute key strategic initiatives, not just report on them.

Strategic Information Capability: The End Game

We believe investments in enterprise systems, data warehousing, and business intelligence are enabling firms to move up the data management maturity model. Through these investments, many firms have been migrating from Facts to Understanding and now into Optimization; however, there is still tremendous opportunity in the next step – Innovation.

Analytics at Work: International Gaming Organization Leads in Data Analytics

When a casino was faced with limited expansion options, management performed an analysis of the existing customer base in order to find growth opportunities. This led to the launch of very successful loyalty and multiple data-driven marketing programs. Over time the firm has employed both data warehouse and BI platforms to support these programs.

With the data warehousing solution, the casino has saved time and money associated with data collection and aggregation. The BI platform and loyalty program have allowed management to analyze customer behaviors such as playing habits, winning and losing amounts, frequency and duration of gaming, number and type of room purchased, as well as dining preferences.

Targeting their ideal segment – the 50+ low-roller with time on his or her hands – the firm focused on developing the customer “experience” to capture additional casino visits and a greater share of wallet. Real-time analytics allowed the casino to further segment this target audience and to empower their employees to improve the customer experience, in the spirit of gratitude and generosity, with, for example, show tickets, meals, and upgraded rooms, which resulted in longer and more frequent visits. After deploying the BI platform, income from operations at two Las Vegas locations jumped more than 25%.

As an excellent example of how analytics can drive strategy, segmentation revealed the opportunity and opened the door to the strategy. Real-time analytics provided the execution capability. In the end, it wasn’t an enterprise system tracking financial transactions that drove the leap in income – it was the investment in analytical capabilities.

Sagence Group Approach

At Sagence Group, we are committed to helping our clients build strategic information capabilities through data analytics and information asset management. We can help you use data analytics to derive value from your information asset. You will have greater ability to identify and exploit analytic opportunities, and we do it in a pragmatic and collaborative way so your organization builds a sustained capability. Depending on the status of your initiatives, the initial investment can be relatively small.

Information Asset Management

Data only becomes valuable information when placed in context. Some of the greatest – and often most untapped – value comes from leveraging the intersections of key processes, organizational silos, and even different organizations. Although these areas of intersection rarely have owners and are commonly ignored, data can provide valuable insights into the interactions and relationships of these separate and/or orphaned entities. Placing data into such new contexts allows examination of an organization’s activities from a new perspective but requires sophisticated technical integration between application and data storage systems. To consistently extract the value, one needs to appreciate the technical complexities and the competing demands involved in managing the data created, captured, and stored within your information asset. To be effective, you need to: (1) treat your information as an enterprise-wide asset and (2) govern it appropriately.

Treat your Information as an Enterprise-Wide Asset

Like any other asset, you need to:

• Understand it – have effective catalogs, repositories, measures of quality and quantity
• Ensure that it is used productively – know which decisions are being informed appropriately and which ones are being underserved
• Ensure that it is planned for and developed appropriately – invest in and enhance the asset to deliver more value

Appropriately Govern the Asset

Due to complexity and competing demands, the only way to manage this asset effectively is through strong enterprise-wide governance.

Governance processes need to:

• Be fair-minded and well-represented, not localized
• Focus on the entire data lifecycle from creation to destruction
• Be supported with feedback on the condition, usage, risk, and cost of the asset

Design and Build

Requirements Definition

• Review business goals and create business requirements
• Identify data sources
• Review current technical environment and strategic direction
• Define technical architecture (data warehouse)
• Create data architecture and logical data model
• Establish sandbox environment; source appropriate sample data
• Create extract, transform, and load (ETL) strategy
• Select tools, software, hardware, etc.

Prototyping

• Set up staging and development environment
• Complete initial analysis efforts; quantify expected benefits
• Validate reports/analysis capabilities
• Define and build ETL processes
• Load and validate data
• Create meta data and physical model
• Create initial user reports, queries, etc.
• Train beta users
• Finalize plans and cost estimates for production release

Production Release(s)

• Get feedback from key constituents
• Scale up functionality and scope
• Set up production environment
• Enhance ETL processes, load data, and validate
• Formalize data committee/ ownership roles and responsibilities
• Build upon initial user reports, queries, etc.
• Conduct user training
• Exploit data warehouse capabilities
• Plan and estimate cost for next phase

Applied Decision Science

Is your organization an analytical competitor?

The following industry perspectives illustrate how analytics can be employed and how Sagence Group can help.

Healthcare providers

Historically, provider data was mainly used to report the past to regulatory agencies for compliance, accreditation, and credentialing purposes. As the use of analytics has gained momentum, many organizations are now using these techniques to improve scheduling of patients and staff, improve coordination of care activities, and monitor patient follow-up. However, analytics still appears to be siloed in clinical and financial organizations. And unfortunately, a significant portion of analytics is still based on administrative data (e.g., claims and eligibility).

Sagence Group is focused on helping our provider clients overcome the obstacles that are keeping them from finding the value in their information. For example, to generate a better view of outcomes, we are committed to helping our clients integrate clinical, operational, and financial analytics using data from encounters, claims, billing, and practice operations. We are also seeing other beneficial trends in the market including:

• The use of clinical encounter data for clinical analytics in place of claims data
• Extending financial analysis beyond claims to billing, procurement, and other general ledger (GL) data elements
• Basic forecasting of capacity, practice development, service development, equipment financing, and infrastructure needs

Product-based companies

Manufacturers are increasingly incorporating “intelligent devices” into their products as a differentiator in the rapidly commoditizing service business. The data collected from these devices is used in a closed loop between product support, product development, and sales to bring new products and service offerings to market. As a result, traditional reactive services are becoming more proactive and new high-value predictive services and products are being offered. Leading companies are generating new annuity revenue streams and increasing existing margins, while building closer relationships with customers and partners through intelligent services.

Sagence Group helps clients evolve from creating stand-alone products and reactive services to innovative, information-based products and predictive services. We focus on ensuring alignment of business needs with technology to ensure the success of the intelligent device program. Our approach consists of four phases which can be executed independently:

• Information Strategy & Planning – Identifies and prioritizes opportunities for information-based products/services
• Adoption & Deployment – Obtains business alignment, connects intelligent devices, and collects data
• Offering Development – Creates, prototypes, and launches new information based products/services
• Decision Science – Provides the measurement, analytics, and change management necessary to take advantage of the field data; potential opportunities include: product development feedback, bundling and up-selling marketing programs and effectiveness; and supply chain performance

We have used this approach successfully in assisting leading medical device and industrial equipment manufacturers in establishing their intelligent device programs.