Here at IBM’s Lean practice we use a diagram called ‘Mississippi’ to analyze demand. It is not so-called because it originates in Mississippi – in fact I’ve been given to understand that this tool was developed, and named, in our UK practice*. Instead, it’s called the Mississippi because, like that great river, demand comes from many different sources (or tributaries) and can leave a process through a number of different points (the delta). And, apparently, at times the Mississippi delta reflects tidal patterns and flows upstream. In the same way, demand can route back into, or upstream within, a process – for example, in the shape of rework.

We want to analyze the volume and frequency of demand for a number of reasons. Understanding demand helps us to:

Step 1 of 7

14%

Which of the following best describes how you currently monitor and manage systems across your hybrid cloud environment?(Required)

Multiple separate tools for different environments

Multiple separate tools for different monitoring and management functions

Single consolidated dashboard

Custom built monitoring and management solution

No full monitoring and management solution

Don’t know

How valuable would it be for your monitoring and management solution to incorporate predictive analytics to help you identify and address system issues that are critical and not waste time or effort working through all the data and “noise” that is not critical?(Required)

Extremely valuable

Moderately valuable

Somewhat valuable

Slightly valuable

Not valuable

How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

An orchestrated response process that leverages automation, AI, and human expertise to rapidly respond to potential issues

Advanced monitoring tools such as predictive analytics and anomaly detection to proactively identify and address potential issues

Respond to issues as they arise, using manual processes and troubleshooting techniques

A combination of automated remediation, orchestrated response, and/or proactive monitoring to address potential system issues

Don’t know

Other

What methods does your organization use to control and monitor cloud/IT spending?(Required)

Centralized procurement processes

Pre-approved budget thresholds

Automated cost monitoring tools

Department-level spending controls

Regular cost audits and reviews

Cloud cost optimization platform

Approval workflows for resource provisioning

Native financial operations tools provided by the cloud provider

No formal controls in place

Don’t know

Other

Please specify:

Which methods do you rely on most to detect security vulnerabilities in your systems?(Required)

Automated scanning tools

Manual assessments

Vendor notifications

Threat modeling (for early detection)

None of these

Don’t know

Other

Please specify:

What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

Based on potential impact

Based on exploitability

Regulatory compliance requirements

Based on CVSS scores

Risk-based analysis of multiple factors

First-in-first-out approach

No formal prioritization process

Don’t know

How do you typically handle system updates and security patches?(Required)

Automated updates and patches

Manually review and apply updates and patches on a regular schedule

A combination of automation and manual review

Apply updates and patches on an as-needed basis.

Outsourced update and patch management

No defined process

Don’t know

Other

Δ

• Identify ‘runners’ (everyday requests), ‘repeaters’ (less frequent, but not unusual requests) and ‘rarities’ (infrequent requests). This might be in terms of user groups, applications, or type of request (for example – small changes vs major project). When we design our improved future state, we will design it for runners and repeaters. Sometimes the impact of exceptions can be so painful, team’s lose sight of how infrequent they are, and design a process to prevent or manage those rarities – which will be inefficient for all those runners and repeaters.
• Identify failure demand – Where are additional requests re-entering the process, as rework? Where is there process activity which doesn’t ‘go anywhere’?
• Illustrate channels in and out of the process, so we can identify potential control points, or illuminate a lack of filter, and see where demand might be routed in via unexpected channels.
• Tell us what we don’t know: which elements of demand are we unaware of? We need to understand all demand so that we can build and resource (load level) a process which can meet that demand. Sometimes finding out what we don’t know is a lesson in itself.

These benefits are as relevant to Lean for DevOps as in any other area.

It’s hard to say what you’ll learn from conducting this analysis, until you’ve done it, as every Mississippi is different. But to demonstrate some of the valuable lessons I’ve learned from drawing up Mississippis, here are some real life examples:

In their different ways, each of these helped make the case for a shortening of the SDLC, closer coupling of development to business demand, and a more nimble deployment process.

*If you’ve seen this in use outside of an IBM engagement, I’d love to hear about it! Find me on Twitter to set the record straight.