Three Critical R&D Mistakes and How to Fix Them

This blog is going to talk about the three most common and critical R&D mistakes and how a software system like Vicinity can help correct them or avoid them altogether.


1) Overuse of Excel - As I travel to clients and prospects I find one of the most used R&D database tools is Microsoft Excel.  Everyone has it and everyone knows how to use it.  The problem is that what once was an efficient method to track R&D products soon grows to an administrative nightmare.

Excel was never designed to store significant amounts of data nor was it designed to share information outside of the spreadsheet.  YES you can do it but with a tall enough hill and enough speed a car can fly.  It is not the take-off that is the challenge, it is the landing.

So come out of Excel and get that data into a database.  When you do that you can mine that data and share information and insights with those around you.

Vicinity provides formula management as well as version control.  Any data you want to track about a formula is filed for easy access.  Once the formula is placed into production R&D can track the effectiveness of that formula via batch tickets that are tied directly to the master formula.  Subsequent adjustments to the formula become a snap once the data is centralized in a database and outside of Excel files with varying formats.

2) Too much reliance on history to predict the future – When developing R&D formulas it is typical for research chemists to obtain the latest material prices from purchasing.  They ask for a list of current prices to ensure their formulas are costed adequately.

While this is a terrific improvement over keeping an external list of items in R&D with costs from the 1990s it is still far from ideal.

Incorporating future costs along with current costs and the review of trends is a more accurate view of the formulation costs.

So keep talking with procurement but instead of asking for the last cost go one step further.  Look at the cost over the past 12 months as well as the trend in the upcoming months.  This change will result in a more realistic cost estimate and better project profitability for the proposed product.

Vicinity formula costs are automatically tied to current the prior cost of each material.  There is no need to contact purchasing for this data.  Instead you can ask them to provide a view into future costs.  Vicinity supports an unlimited number of proposed costs for a component.  This allows a research chemist/nutritionist the ability to cost a formula based on current inventory values but also anticipated trends into the future.

3) Sticky notes won’t cut it – Unless you just like working from scratch most research chemists will leverage work already performed to help build a basis for a new formulation.  If you have already done something similar why recreate the wheel?

The challenge is remembering (or finding) what the R&D lab has worked on before, the results of bench tests and acceptance by the customer market.  If only you had that data available to search.

Well it never gets built unless you start building it today.

It is not practical to think you can archive all the work you have ever done.  But you can start archiving today.  Make a list of the key search criteria and get that data into a structured format (NOT EXCEL) so you can search on that data in the future.  Before you know it you will have quite the database of formulas to choose from. In all your spare time you can work backwards entering old formulas into your new data goldmine.

Vicinity out of the box has the ability for a user to define an unlimited number of search fields.  We call these attributes.  These attributes help you describe the formula in way that will help your future-self find the formulas you created in the past.  All this without a bit of programming.