Custom spreadsheet solutions which survive long after the developer has "left the scene", are often those which users accept because they discover it _ among other benefits _ makes their work quicker and easier to do. That is why the best person to develop such solutions tend to be one who works in that area, and is therefore familiar with the way the manual system operates. S/he would have an "insider's" perspective of the best way to introduce automation other users will readily adopt _ even as it solves the identified problem(s).
Variable Costs Control/Reduction was a strategy that worked extremely well for the company. Most memorable for me as a brewer, was the manner in which huge monetary savings/profit gains were made by successfully implementing variable cost reduction initiatives. For instance, a brewing ingredient switch was made to a more readily available local alternative which was many times cheaper, resulting in phenomenal savings and progressively increasing profit earnings even though the price of beer produced was not raised. This practice was routinely applied across the brewing and packaging processes in line with a well thought out plan.
In effect what I am saying is that companies which get the most value from spreadsheet automation(including using it to avoid expenditure on less adaptable commercial off the shelf applications) will be those which empower their users to routinely generate "in house" solutions. In such companies, you will find that only when the requirement becomes considerably specialised or complex, does the IT department get called upon to develop or purchase software solutions for user departments or functions with significant data recording and analysis needs.
You will find this article of considerable reading value, if you belong to at least ONE of the following spreadsheet user categories: Owners of Small Businesses _ Restaurants/Bars, Hotels, Hospitals, Factories, Consultants etc; Decision Makers/Job Holders in Corporations _ Materials Managers, Sales/Marketing Analysts, Financial Analysts/Accountants, Project Engineers; And Anyone desiring to make BETTER sense _ and use _ of data!
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