It's time to break the bottlenecks

When heavy industries first started their digitalization efforts in the mid 1980s, computer spreadsheets were borderline magical. They simplified workflows, enhanced data exchanges, reduced the need for math skills, and accelerated business development.

The world has since moved on. The complexities of modern supply chain management have long since crystallized the need for purpose-built digital solutions, and the shortcomings of spreadsheets are becoming steadily more apparent: 

1. Limited capacity

Excel has limitations on the number of rows and columns it can handle. For instance, in Excel 2019, you are limited to 1,048,576 rows and 16,384 columns in a single worksheet. Supply chain datasets often exceed these limits, leading to data truncation and loss of critical information

2. Growing pains

Performance degrades significantly as the size of a workbook grows. Complex calculations and data manipulations can lead to slow response times, making it impractical for real-time analysis and decision-making.

3. Not enough decimals (yes, really)

A limit of 15 decimal places can lead to rounding errors when dealing with extremely small or large numbers. Such inaccuracies can be problematic when calculating financial values or optimizing complex supply chain models.

4. Import/export trouble 

Anyone who’s tried to export or import data from Excel or other spreadsheet solution know that formatting, data loss and compatibility issues are far too common. 

SO MANY QUESTIONS: Excel is a great and powerful tool. But it was never made to be the center point of your supply chain management.

5. All that bad data (this is a big one) 

Ensuring data quality through validation rules and data cleansing procedures is cumbersome in Excel. Supply chain data often requires stringent validation, which can be prone to manual errors and omissions.

That's one of our core focus areas. Check it out.

6. Analytic shortcomings 

Complex supply chain analytics, such as predictive modeling, machine learning, and Monte Carlo simulations, are beyond Excel's capabilities. You need custom coding to do that properly.

7. ERP-friendly? Not at all 

Integrating Excel with enterprise resource planning (ERP) systems, warehouse management systems (WMS), and customer relationship management (CRM) systems can be challenging and may require custom scripts or middleware.

8. Scalability issues 

As the supply chain expands, managing Excel workbooks for multiple products, locations, or supply chain nodes becomes unwieldy. Handling different scenarios or production configurations can lead to an explosion of spreadsheet complexity.

9. It's simply not safe 

Excel files lack robust access control and auditing features. Ensuring data security, compliance with data privacy regulations, and monitoring user activities is challenging without dedicated data governance tools.

10. Version multiverse 

Managing multiple versions of Excel files in a collaborative environment will lead to version control issues, difficult to track changes and understand the history of data modifications.

11. Mayhem ripple effect 

When errors occur in one part of a complex Excel workbook, they can propagate throughout the entire document, leading to extensive debugging efforts and potential data corruption. We call that the bad data ripple effect.

The solutions we offer tackle all those issues. Consider the wider picture: How the reliance on software that is clearly not designed for supply chain management leads to loss of time, money, unnecessary orders, overstock, is detrimental to ESG targets and can be a cybersecurity risk for anyone using it.

 We love Excel. For intended purposes, it’s a life saver and super practical. It’s just not meant for supply chain operations, to replace proper databases or be an operational centerpiece.

The solution might be something totally new. Or something in between.
We have experience with both. Let’s talk.

#digitaltransformation #excel #supplychainmanagement