Tran Decision Making: Why the last mile of analytics should be your first priority? by Anh Tran

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The Significance of the Last Mile of Analytics: Making It Your First Priority

Hello inquisitive minds! I am Ann, a devoted data analyst and data scientist enjoying a thriving career spanning over 11 years across a diverse range of industries such as finance, technologies and wholesale in Vietnam, Singapore and the Netherlands. Today, I am about to shed light on why the 'last mile of analytics' should be your very first priority.

Our Culinary-inspired Agenda

Just like a meal at a restaurant, our session today has four primary components:

  1. Understanding what the last mile in analytics is
  2. Unraveling the reasons you should care about it
  3. Predicting what could happen based on the choices we make
  4. Collating the key takeaways

The Dire State of Data Science Projects

Regrettably, a massive 87% of data science projects never see the light of day in terms of reaching production, according to a recent shocking study. This revelation prompts us to dig deeper into why it is so.

Why So Many Project Failures?

In an attempt to decode this mystery, we journey through the typical analytics process. The process usually begins with a business problem, then moves to data examination, followed by infrastructure and analysis, and finally winds up at the stage of presentation. Unfortunately, several projects falter at this stage due to a lack of knowledge sharing, difficulty in communicating the intricate data science components to stakeholders, or in some cases, the results not reaching decision-makers. For the projects that do secure stakeholder buy-in, transitions could still lead to failure.

The Last Mile in Analytics: A Closer Look

Broadly speaking, the last mile in analytics bridges the gap between the analytics result and the action taken thereafter. From a bird's eye view, it's the ultimate step to reach the target. However, it fails to fulfill the void between the analytics outcome and the action taken because of that analysis.

What Happens When We Take Certain Actions?

While there are no firm stories about the consequences of adjusting the last mile of analytics, a study by McKinsey compared top-tier companies with average companies and discovered commonalities among the top-tier leaders. They found that these company leaders heavily invested in three critical areas: aligning strategy, creating the correct data technology and people foundation, and conquering the last mile. Substantially, they showed a higher level of commitment to bridging the gap between analytics and action.

Learning from Failures and Making Calculated Decisions

Drawing from these observations, what should we do differently? Emulating 'Best Suited' practices tailored for specific company stages and industries could be a solution. To counter the ongoing challenges, you could:

  • Prioritize business adoption as a key metric.
  • Share failures and study the reasons behind them.
  • Involve stakeholders early and maintain frequent communication
  • For each business question, assess if complex analysis is called for
  • Adopt data metrics for data governance
  • Executed the most impactful decisions, especially related to data infrastructure, first.

The path to closing the gap in analytics or strengthening the last mile requires a strategic approach where we start with the end in mind. This can be achieved by making business adoption an essential metric, involving stakeholders early, frequently updating them, and making the most impactful decisions.

In conclusion, it is important to understand the potential costs when deciding to invest in infrastructure.

Thank you for attending the session, I look forward to hearing your feedback. Stay inquisitive and continue expanding your knowledge!


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