November 2017 | Seabrook Technology Group

Monthly: November 2017

Integrated Knowledge

Enterprise Intelligence that Drives Operational Excellence: Part 4 – Integrated Knowledge

By | Blog | No Comments

Truly integrated knowledge is more than just reporting. It is a concept for providing the capability to share data across applications and intelligence functionalities enabling a “best of breed” approach and can maximize the value each system provides. Allowing applications to access and leverage BI Models can maximize the value that the intelligence brings to the organization. Integrated knowledge also allows an organization to constantly feed the intelligence gathered back into their systems to drive excellence.

You must unlock your data to allow it to drive your systems, processes, and business. This data more than likely resides across many applications. This data already exists in your system, whether it resides in Excel spreadsheets or maybe it is hand written somewhere, and it needs to be submitted electronically. The point is that more than likely, this information already exists within your organization. With the proper technology coupled with an effective strategy, data can now add endless value to your business as opposed to being a hinderance.

It takes planning and design effort to implement an effective integration solution into your organization, but it is critical in order to truly drive operational excellence. This is why it is so important to have an Enterprise Intelligence Strategy and an Enterprise Integration Strategy to leverage.

To learn more, click here to request a whitepaper on the topic.

Enterprise Intelligence Strategy & BI Strategy/Definitions

Enterprise Intelligence that Drives Operational Excellence: Part 3 – Strategy & BI Strategy/Definitions

By | Blog | No Comments

What does the Enterprise Intelligence Strategy really look like? The strategy content will be different based on each organization’s goals, processes, and situation. However, if we were to encompass all of the previous identified needs we would want to insure that a consistent set of criterion were included. It is important to define the goals, approach, and use of the intelligence in order to define what data will be included and how it will be provided. Also, to insure that the data is actionable, it is important to highlight the actions and business logic that needs to be in place to appropriately support the organization. This will help determine the technology sectors to be put into place and which BI models are needed. If you start with the Data, Applications or even BI Models themselves, you may not have chosen the appropriate technology for your organization. Starting with the Strategy, and BI Definition enables you to discover what the organization really needs, how it will be used, and creates the requirements for the technology sectors of your Enterprise Intelligence Solution.

When looking at the overarching strategy, people usually start with KPIs (Key Process Indicators / Key Performance Indicators) that show how an organization is performing. Often, these KPIs will be related to financials, efficiency and/or yield. It depends on the particular target area you are putting your Business Intelligence in and it would also encompass any definitions. For instance, some people calculate yield differently and therefore it would use the target area’s definition for yield calculations. Some want global yield, some want process yield and some want to know overall yield through multiple operations. They want to accumulate this knowledge to understand min/max lead times for reasons such as informing their customers of the time difference from ordering to receiving a product or how quickly do they need to be responsive to the change in market. This strategy and solution do not have to be solely focused on manufacturing processes; it could encompass many business functions such as quality release, order processing, planning, supply logistics, etcetera.

To learn more, click here to request a whitepaper on the topic.

Enterprise Intelligence Operational Excellence

Enterprise Intelligence that Drives Operational Excellence: Part 2 – What it is and Why do you need it

By | Blog | No Comments

“The Execution of a Technological Strategy enabling integrated process and environmental knowledge to be leveraged in standard practices to accomplish operational excellence.”

– John Dzelme

It seems every organization has its own definition of what Enterprise Intelligence might be – some organizations claim it is an educated work force, others may say it is an application such as business objects or analytics reporting capabilities, or whatever other applications people use for data analysis. Some organizations claim Enterprise Intelligence is the ability to put their metrics on big screens so everyone has visibility to the overall health of the process. Some people say it is the historical data that they have, the equipment level data or the product level data, or that it is the customer data that really encompasses Enterprise Intelligence.

Seabrook have concluded that it is all of the above and more. It is really about turning all of the data into value. We have found that, independently, none of these aforementioned claims really create value. It is only when one can obtain appropriately contextualized data, through the appropriate medium and couple it with the right technologies and business systems, can they start to turn that data into prime value for the organization.

By pulling all the data together and leveraging it into standard practices, you can achieve operational excellence.


To learn more, click here to request a whitepaper on the topic.


Enterprise Intelligence that Drives Operational Excellence - Setting the Stage

Enterprise Intelligence that Drives Operational Excellence: Part 1 – Setting the Stage

By | Blog | No Comments

“After all, data that doesn’t do anything is just data; Data that drives action….is intelligence.”

– John Dzelme, 2013, Big Data: Business Executive Series Conference

The hype behind Big Data really is driven by the potential value that Big Data can provide for organizations. The basic premise is that with the appropriate enterprise intelligence strategy and appropriate complementary technologies, an intelligence solution can provide significant returns on investment.

Organizations are interested in intelligence capabilities and how Big Data allows them to have a competitive edge or how it can drastically reduce cost of goods sold. It is also important to understand the different stages of data and how data can be leveraged within an enterprise for specific initiatives, especially those that promote and enable a continuous improvement culture. The danger and horror stories around poorly executed Big Data implementations are typically those that do not take a holistic approach to the solution. Instead, some organizations make the perilous mistake of focusing on just the data, or just the technology, or even just a specific application.

Unfortunately (contrary to popular belief and application sales literature), there is not a single application on the market that can provide a complete end-to-end Business Intelligence (BI) Solution. An organization’s data is spread amongst many data sources with different contexts. In addition, the real power of data is lost if it is not capable of being used in applications for decision making.


To learn more, click here to request a whitepaper on the topic.