During analysis and exploration, analysts will use many different types of charts in slightly different ways, because they try to find something in the data. However, when they find a meaningful insight, they should use different, more specific charts for presenting to users, designed for ease of interpretation and impact.

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The information system’s goal of mimicking the structure of the business processes allows users to understand what happens and make decisions accordingly. Sometimes users will ask for specific reports they need short-term, but one must see beyond that. When modeling business events (with facts and dimensions at the lowest grain), that would already cover the reports they wanted (and many others). By modeling business events, one enables a plethora of insights, anticipating the most common questions.

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The “potential” value of the data in the lake comes from having it available for advanced data science analytics and further processing (such as Artificial Intelligence, Machine Learning, etc.). These usually produce a structured result, which the team can then feed into the data warehouse or reporting for user consumption. The “actual” value of the data gets realized when a business user can apply it to making a decision, not before.

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In a growth mindset culture focused on learning, executives do not expect people to blindly follow decisions that might lead to the wrong outcomes. They expect the teams to use data as part of performing actions to assess impact, and if someone learns that the decision might lead to problems, they expect the team to speak up and avoid those negative consequences. They don’t want anyone justifying later with, “I was told.” They expect everybody to proactively bring value and challenge the status quo.

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Reaching a target means that the team appropriately planned the “who does what and how by when,” given the guiding priorities and strategies. Conduct analytics to identify constraints on missed targets. Maybe the team needs more people, time, investments, or a different process. Focusing analytics on the causes for missing the previously planned targets will inform future planning, options and course corrections. This defines learning.

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While finding great new talent, don’t forget to regularly re-recruit people you already have. In recruiting, part of the process is taking time to explain why they should want to come work with you. This isn’t an activity only for recruits. Tell your people why they are valued, and make sure they understand why they should continue working with you.

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Design security in from the start, so it improves speed. Help teams understand how to be secure, so security never slows them down. Empowering teams to use security tools themselves limits the risk of finding security issues too late in a release. Tools such as code review tools can be automated into every test pass during sprint team iterations. Leverage templates and scripts to ensure security controls are active and operating as expected.

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Can you combine data you already have to create new value? Is there a business model hidden in what you discard? For example, we had years of enterprise sales opportunity data. We were about to purge it since all the opportunities were long past. Then we discovered the data was useful to train a machine-learning model that accurately predicted success of any new sales opportunities. This opened up many new ideas.

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Historically, IT measured success using compliance, uptime, and delivery: on time, on scope, on budget. These are still worth tracking, but should not define success. It’s the wrong incentive for IT to deliver just what is asked of them. Instead, define success based on bona fide business improvement, not IT delivery. And measure end-to-end processes working as expected, not uptime of IT services.

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Transformation is not going faster with the same historical IT practices, or getting more done by just working longer hours, or adding capacity with more lower cost resources. Don’t just overlay what teams knew historically on top of Agile practices. Using shorter waterfalls completely misses the point. Fundamental change is required. Dedicated coaches can help teams really transform faster.

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