Analysis Report Four - Trend Analysis and Value Creation

Executive Summary

Technology has changed the way organizations create value for customers. Instead of only selling products or services, many businesses now create value by connecting customers, suppliers, and other organizations through digital platforms. Every interaction on these platforms creates information that can be used to better understand customers, improve operations, and support future business decisions. This report explains how platforms and trend analysis work together to help organizations create value over time (Parker, Van Alstyne, and Choudary 2016; Eisenmann, Parker, and Van Alstyne 2006).

Trend analysis allows organizations to look beyond a single report by examining how information changes over time. Looking at trends by year and then drilling down to months provides a better understanding of business activity and helps managers identify patterns that may otherwise go unnoticed. Organizations should continue using trend analysis alongside platform technologies because it supports better planning, stronger decision-making, and long-term value creation.

Introduction

The way businesses operate has changed a lot because of digital platforms. Traditional businesses mainly create value by making and selling products, while platform businesses create value by bringing different groups of people together in one place. As more people begin using a platform, it becomes more useful because there are more opportunities for customers and businesses to interact. This idea is called a network effect and is one of the biggest reasons platform businesses continue to grow (Parker, Van Alstyne, and Choudary 2016).

With that being said, platforms would not be nearly as valuable without data. Every order, purchase, or customer interaction gives organizations information they can use to better understand what is happening in their business. Rather than making decisions based on assumptions, companies can look at trends over time to understand customer behavior, improve performance, and make better decisions for the future.

Outside Research

Many successful companies rely on digital platforms because they allow businesses and customers to interact more efficiently. Companies such as Amazon, Uber, and Airbnb continue to grow by creating systems that become more valuable as additional users join the platform. Research shows that these network effects help organizations strengthen customer relationships while creating new opportunities for growth and innovation (Parker, Van Alstyne, and Choudary 2016).

One way organizations continue creating value is by using trend analysis to better understand how performance changes over time. Looking at historical trends allows managers to improve forecasting, prepare for changes in customer demand, and make better operational decisions. At the same time, organizations must ensure that the data they collect is accurate, secure, and reliable because poor-quality data can lead to poor business decisions (McKinsey & Company 2023).

Data Visualizations

The first visualization looks at total revenue across several years to get a better idea of how the business has performed over time. Starting with the larger view makes it easier to notice whether revenue is generally moving up, dropping, or staying around the same level. Managers can use this information as a starting point before looking into the smaller changes that happened within each year.

SELECT strftime('%Y', Orders.OrderDate) AS Year,
       SUM("Order Details".UnitPrice *
           "Order Details".Quantity *
           (1 - "Order Details".Discount)) AS TotalRevenue
FROM Orders
INNER JOIN "Order Details"
ON Orders.OrderID = "Order Details".OrderID
GROUP BY Year
ORDER BY Year

ggplot(data = myquery1,
       aes(x = Year,
           y = TotalRevenue,
           group = 1)) +
  geom_line() +
  theme_minimal() +
  labs(
    title = "Total Revenue by Year",
    subtitle = "Overall revenue trend over time",
    x = "Year",
    y = "Total Revenue",
    caption = "Source: Northwind Database"
  )

The second visualization focuses only on 2022 and breaks the revenue down month by month. A yearly total can hide a lot of smaller movement, so this graph gives a clearer look at when revenue changed during the year. Seeing those monthly differences can help managers understand whether certain parts of the year performed better and where more attention may be needed. During the live edit, the graph shifted from month by month to day by day to represent the drill down process.

SELECT strftime('%d', Orders.OrderDate) AS Day,
       SUM("Order Details".UnitPrice *
           "Order Details".Quantity *
           (1 - "Order Details".Discount)) AS TotalRevenue
FROM Orders
INNER JOIN "Order Details"
ON Orders.OrderID = "Order Details".OrderID
WHERE strftime('%Y', Orders.OrderDate) = '2022'
AND strftime('%m', Orders.OrderDate) = '01'
GROUP BY Day
ORDER BY Day

ggplot(data = myquery2,
       aes(x = Day,
           y = TotalRevenue,
           group = 1)) +
  geom_line() +
  theme_minimal() +
  labs(
    title = "Total Revenue by Day during January 2022",
    subtitle = "A closer look at revenue throughout one Month",
    x = "Day",
    y = "Total Revenue",
    caption = "Source: Northwind Database"
  )

Recommendations for the Industry

There is more value in data than simply collecting it. Businesses should spend just as much time looking for patterns and trends as they do gathering information in the first place. When managers understand how things are changing over time, they can make decisions with more confidence instead of reacting after problems have already happened. Trend analysis gives organizations a chance to recognize problems early and make adjustments before those problems begin affecting performance.

Another area companies should continue improving is how they use trend analysis during planning. Looking at information throughout the year gives a much clearer picture than relying on one report or one point in time. Small changes may not seem important at first, but over time they can reveal larger patterns that help businesses improve forecasting, manage resources more effectively, and better prepare for future demand. Combining platform technologies with consistent trend analysis allows organizations to create more value for both the business and its customers while making stronger long-term decisions.

References

Eisenmann, Thomas, Geoffrey Parker, and Marshall Van Alstyne. 2006. “Strategies for Two-Sided Markets.” Harvard Business Review 84 (10): 92–101.

McKinsey & Company. 2023. “The Value of Digital Platforms and Ecosystems.”

Parker, Geoffrey G., Marshall W. Van Alstyne, and Sangeet Paul Choudary. 2016. Platform Revolution. W. W. Norton.