Recently when discussing this topic with a colleague I used this image as a basis of discussion on the types of information and data we cover with our Information Management capabilities.
Since “information” is a pretty broad word, I’ve been trying to understand what we mean when we say Information Management. Here’s what I’ve learned, the numbers are aligned with the numbers in the screenshot.
- We mean structured data like what we are familiar with in application systems. Customers, products, sales orders, etc. All the data that is stored in a central database that is used by the application system. Of course this includes the ability to manage the master data, cleanse, enforce data quality, as well as the ability to extract, load, and transform the data as required.
- Office documents like word, excel, and other desktop word-processing applications. This data is stored across the enterprise, on share drives, laptops, much of it not controlled at an enterprise level. This content may be critical to the application data, and so we need to manage this content with the same importance as the structured data in the database.
- Pictures, scanned documents, and other images. These could be scanned invoices, pictures of products that are sold in a catalog, drawings of products that are being designed and built. These become part of the content that needs to be managed and related to the structured data when required.
- Information that is available in XML format, such as RSS feeds, blogs, and other semi-structure information that is important to the enterprise.
- It might be hard to read in the screenshot, but number 5 reads “The car should self-drive on the highway”. This piece of information may come from a survey, it might be a comment on a website, and by itself it might not be important. However, if you are looking at car design over the next five years and 60% of the comments you receive have something about self-driving, then this comment warrants further investigation. So, information management also includes looking into text we receive and doing some analysis to determine sentiment, feedback, input, or action that should be taken based on comments.
- Number 6 in the screen shot is a list of flights that have landed or are about to land at the Frankfurt airport. This is meant to represent transient data. What is meant here is data that is short-lived, or data that is important as it is correlated to other data / information. For example, if my returns in a certain week are up, and my quality numbers are low over the past three weeks, maybe those two are related, so we can track both and notify if we see a trend that requires investigation. In the flight example we might want to look at trends at flights departing on time with security level monitoring so we can determine when the security is at a certain level flights can be delayed by a certain percentage of time.
When we say “Information Management” we mean the combination of traditional structured data and non-structured information. Our interest is from the moment of creation thru retirement. The retirement of data and information has the same value as creation. Once information is no longer needed, it becomes a liability, that could be a legal liability, cost liability, or other liability. The entire lifespan of the data and information is covered within Information Management. As we manage all this information, it is critical to have some governance surrounding the management of our data and information, this is referred to as “Information Governance” and you can see it has a role with all the types of information from creation to retirement.
If you’re interested in this topic, let me know and I can publish a blog that maps each of the types of information we cover to the solutions / products that are used for the information and when to use each capability.
So, how does this compare to process & workflow management? The connection is closer than I first realized when moving to the EIM solution management team. At a foundation level, the processes we execute assume the data is good- it is cleansed, it is valid, it is ready to use. Information Management provides this ‘trust’ in the data. From the perspective of how they work together, here are some examples we are seeing today:
- The structured data must be cleansed and there must be a level of data quality for the process. Greg Chase recently published a Podcast: How SAP IT Uses BPM and Data Services for Post Merger Data Migration where he covered how SAP used a combination of our Information Management solutions (using Data Services) with NetWeaver BPM for the Sybase acquisition.
- When managing the content such as documents, images, there is normally a process that accompanies the scanning of documents, approving, and associating with the business object (for example, scanned invoices). Historically this has used our business Creating your first SAP Business Workflow.
- The correlation of data & information that causes an action or intervention will use process & workflow management to ensure the action is taken and to put a process around dealing with the outcomes of trending, correlating information. Check out this perfect order demo and defective product demo that were done for Sapphire. These are done under the theme of “Operational BI”, which includes business intelligence, information management, and business process management capabilities.
Because the connection is so strong, it makes complete sense for workflow and process experts to look at Enterprise Information Management as the next place to expand their skill-set and knowledge base.