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Introduction to Inventory Forecasting | Blog | Datarithm

Datarithm Team February 06 2024

Are pharmacies still reliant on a single individual to manually manage inventory? Is this individual extensively experienced in this process, utilizing a spreadsheet-style "database"? Concerns arise regarding the susceptibility to numerous manual inputs, data manipulations, and a growing lack of precision, leading to errors that are challenging to detect and rectify over time.

This outdated approach could potentially incur significant financial losses for any pharmacy. It involves multitasking, manual labor to execute simple plans, and neglects the overall organizational inputs. Worries persist about catastrophic data loss due to accidents, injuries, or personnel turnover. Surely, there must be a more efficient alternative!

Relying on manual methods for inventory and ordering exacerbates the complexity of the process. Access to order and sales history is severely restricted, often limited to only the most recent cycles. This limitation hampers data availability, complicates manual analysis, and hinders the identification of factors driving irregular sales patterns. The task of sifting through available information becomes arduous.

It's widely acknowledged that the farther back accurate records extend, the more reliable the basis for predicting trends. Delving into inventory history often reveals patterns that offer insights into future demands, such as seasonal fluctuations or holiday sales spikes. However, a manual approach alone is insufficient to devise a targeted ordering strategy and maintain optimal stock levels for maximum profitability through effective inventory management.

Dispensing history plays a crucial role in determining stock items and quantities, as well as timing orders. The evaluation process for these factors significantly impacts efficiency and profitability. In most cases, minimizing human error is paramount for efficiency and cost-effectiveness.

Regardless of the inventory and ordering system employed, predicting the first use of a medication is virtually impossible. However, seasonal patterns, like increased demand for allergy medications during spring and summer, can be anticipated and planned for. Manual ordering and inventory management complicate this process, diminishing the effectiveness of predicting product needs and quantities. Inventory forecasting software offers a streamlined alternative.

Managing sporadic product sales poses its own challenges. While there may be a known demand for certain items, their sales occur irregularly, requiring careful tracking to avoid expiration or overstock issues. This necessitates a mechanism, either manual or electronic, to monitor expiration dates and return policies.

Inventory stands as a pharmacy's most valuable asset and a primary determinant of profitability. Effective inventory management is essential for maximizing profit and minimizing risk. Various methods, including algorithm software, help mitigate inventory-related risks by analyzing usage patterns and historical data. Datarithm provides advanced algorithmic solutions tailored to pharmacy operations, integrating seamlessly with existing management systems to optimize decision-making and achieve service, return, and profit objectives.

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