Historically, the investment of land has been made through experience, market knowledge, through planning observation and property trends. Although these factors still remain important, technology is now affecting how decisions are made in land investment more than ever.

One of these major technological changes involves predictive analytics, where patterns and trends are identified through data analysis for future decision making.

In the land development industry, predictive analytics have an increasingly important role when assessing land value and potential for planning future demands.

What is predictive analytics?

Predictive analytics refers to analysing data to predict future results.

Instead of only assessing what has already happened, predictive analytics focuses on using data patterns to make predictions about future events. In land development, predictive analytics allows investors to determine how likely their project will be successful.

Though this does not guarantee outcomes, it still allows for evidence-based decision making, leading to more accurate solutions.

Future land value prediction

Land values are influenced by factors, such as planning policy, investment in infrastructure, housing demand, and economic conditions.

Using predictive analytics enables developers to determine the impact of each variable on land prices through analysis of:

• transaction history
• planning approvals
• infrastructure investments
• population trends
• surrounding market activity

In these cases, land near infrastructure developments or within growth areas, could be of higher value to a developer in the future, compared to land without.

Planning probabilities

Uncertainty remains a major issue in determining planning outcomes. It may be expected that a particular site is suitable for development when it might still be open to delays or rejections based on planning policies and council objectives.

The use of predictive analytics enables investors to analyse planning probabilities and trends within an area, as well as past decision making processes.

This can help identify:

• councils facing growing pressures for housing delivery;
• locations where residential density is rising
• areas experiencing policy changes or allocation reviews
• trends in successful planning applications

While planning approvals are always going to include some level of professional judgment, it can certainly serve as an extra layer of insight.

Identifying future demand

Successful land investment depends not only on planning potential, but also on long-term demand.

More developers are beginning to turn towards predictive analysis when it comes to demographic and economic trends, as it allows them to determine where future demand for housing may occur.

This can include reviewing:

• migration and population growth
• employment trends
• cost of living factors
• travel and transport access
• housing shortage issues

Areas with stronger long-term demands often become increasingly attractive for future development.

Long-term investment planning

Another important strength of predictive analysis is its potential for strategic planning over an extended period of time.

Rather than focusing only on sites with immediate opportunities, developers can assess how areas may change over five, ten, or even twenty years. This encourages longer-term investments and thus greater strategic land gains.

For investors, this can improve:

• portfolio management
• investment timing
• risk assessment
• investment decisions

The idea is not just to respond to changing conditions, but also to make predictions about future developments.

Technological platforms

Predictive analytics relies on the ability to process and analyse large amounts of information efficiently.

Enterprise technology platforms offered by organisations such as Oracle Corporation enable developers to work with data from financial sources, as well as from market analysis and operational reports.

This creates stronger visibility across all projects and provides more advanced analysis than could be done manually.

Data or professional judgement?

Whilst predictive analytics does have many significant advantages, it cannot replace experience and local knowledge.

Land development remains influenced by political, public opinions, market conditions, and site locations that cannot always be fully predicted through data alone.

In most cases, the best thing to do would be to take a balanced approach where predictive analytics and professional judgment are combined.

Conclusion

Predictive analytics is a crucial part of current land investment strategy. Analysing trends in planning, land valuations, infrastructure developments, and market demand helps developers to act strategically and plan future solutions.

With advances in technology, predictive analytics is likely to continue playing an even more prominent role within the industry. Future articles, will focus on the role of artificial intelligence in land sourcing, portfolio management using integrated digital platform, and the impact of technology on property development.