INBOX INSIGHTS, January 31, 2024: New Tech Doesn’t Solve Old Problems, Fact Checking Data - Trust Insights Marketing Analytics Consulting

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New Technology Doesn’t Solve Old Problems

New technology doesn’t solve old problems. It doesn’t. If anything, it exacerbates existing issues by adding complexity or masking underlying problems. If you have problems with your purpose, people, process, platforms, or performance, the solution is not layering more tech on top.

We’re seeing this play out in a lot of companies right now. Instead of digging into why a person or team is underperforming, they are getting replaced with AI. The team may not even be underperforming. Maybe the leadership team is the problem. So they replace everyone with some kind of tech.

This is not the solution. New technology doesn’t solve old problems.

How can you determine what problems your company has? Use the 5P Framework to do a quick audit and see where you need to focus.

Lack of Purpose and Goals (Purpose):

What is the problem we’re trying to solve? What is the question we’re trying to answer? A lot of companies get so wrapped up in the “big idea” that they forget to tie it back to reality and break it down. If you’re setting goals, make sure people know why. Does it align with your mission and objectives? Are those clear to everyone? Introducing new tech will only cause more confusion if your purpose isn’t clear.

Lack of Communication (People):

Effective communication is important in any situation. However, in a business setting, it is essential. The larger your company is, the easier it will be for communication to break down. As a result, people rush around, make quick decisions, and forget to talk to one another. A breakdown in this area can lead to misunderstandings, inefficiencies, and a disjointed workforce. New tech can facilitate communication but can’t resolve underlying issues like siloed departments or a lack of open dialogue.

Lack of Repeatability and Scale (Process):

Technology is most effective when it enhances well-thought-out, efficient processes. It’s about creating a flow that technology can streamline and scale, not replace. When processes are poorly defined or outdated, it leads to inefficiency and confusion. Implementing new technology in an environment with weak processes can exacerbate these issues.

Lack of Governance (Platform):

What the heck is in the system? Who owns it? Who is maintaining it? Without proper governance, decision-making can become erratic and uncoordinated. If you’re not clear about what information lives in your existing systems and how you’re using them, new tech won’t solve that problem.

Lack of Accountability (Performance):

Effective performance requires a clear understanding of individual and team responsibilities. You need to establish clear expectations and key performance indicators. When accountability is absent, how can you know your progress? Introducing new technology cannot instill a culture of accountability.

Regardless of how big or small you think the impact of new tech will be, you need to first be aware of existing organizational issues. Use the 5P Framework to run through each team and the company as a whole. Once you’re feeling confident that you’ve addressed the major issues you can go ahead with your new tech.

When was the last time you did an audit of your company? Reply to this email to tell me or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the impact of generative AI on job security and its role in the corporate world. They debate the consequences of replacing human roles with AI, emphasizing the risks and short-term thinking involved in such decisions. The episode explores the evolving nature of content creation and the necessity of human creativity in the age of AI. Listen to gain insights on balancing AI integration with human expertise in the workplace, and the importance of staying adaptable in a rapidly changing job market.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we examined basic diagnostic reporting from Google Analytics 4. Catch the episode replay here!

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One of the things that is common in any news cycle, but especially during political cycles like elections, is bold claims made with numbers and data. “Restaurant prices have doubled since 2019!” and “Inflation has gone sky high!” and other claims. We aren’t going to deal with politics at all, but this is a good opportunity for us to discuss the citizen analyst – and how it can inform and improve your marketing.

When I hear someone make a claim using data, my first instinct is to ask for a source. What’s the source of that data? And if it’s a person or source that I don’t feel comfortable asking (because who has time to argue on the Internet all day?), then I’ll go get the data myself.

Let’s tackle the claim about restaurant prices doubling since 2019. Is that actually true? How would we know? With the help of generative AI-powered search engines like Microsoft Bing or Perplexity.ai, we can identify credible sources of data. Here’s one from The Economist, the price of a Big Mac in every nation over the last quarter century.

About a decade ago, IBM pioneered the concept of the citizen analyst with tools like IBM Watson Analytics, which unfortunately never took off to the extent they wanted it to. However, in the era of generative AI, doing “citizen analysis” is much more practical because AI tools can perform complex analysis without requiring you and I to code or perform other complex analysis.

Let’s take the example of the Big Mac pricing data from The Economist:

You’ll note that the prompt doesn’t contain any advanced statistical knowledge or techniques, just a clear statement of what we want to achieve. After doing its analysis, ChatGPT had this to say:

Broadly, then, the prices of a signature dish at the McDonald’s restaurant chain have NOT doubled since 2019. Is there anywhere this claim that restaurant prices have doubled is true?

Yes, in Argentina, from the dataset – at least in terms of the price of a Big Mac, restaurant prices have doubled since 2019.

What this exercise shows is that, with the help of data you acquire from credible sources and tools like ChatGPT’s Advanced Data Analysis, you can investigate claims made about data.

This is a great exercise to do, not only for fact checking what news sources and public figures say, but for also proving or disproving claims about numbers in general. For example, you’ll often hear marketing claims like “email has the highest ROI of any channel” or “the average engagement rate on YouTube is XYZ” or “XYZ has the highest CTR of any ad category”. With the right data and tools you have access to, you can investigate this for yourself and see if the claims are actually true, then change your marketing strategy based on your findings.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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