Where ISVs are getting it wrong

Written by Jesse Lard – posted by Bulldogblair

Are you struggling to differentiate yourself from the competition?

Enterprise Resource Planning (ERP) vendors sell fairly complete solutions, but there are many things they don’t do well. That’s where Independent Software Vendors (ISVs) come in, to fill in the information gaps in order to create a more complete picture of predictive analysis.

Here’s an example:

Joe has a jewelry distributorship that purchased an ERP for accounting and pricing. The problem is, it’s incomplete. He needs to easily adjust the pricing of precious metal-based products on a frequent basis in order to sell it competitively. Joe decides to go with an ISV which sells Joe an add-on product that can painlessly adjust the pricing of these products daily.

However, the ISVs solution may still have a gap in it as it relates to improving profitability for Joe’s future pricing. Joe would like to take advantage of the up-swings and reduce his risks during downturns. This means Joe needs the ISVs software to predict the future also.  The predicted future pricing would allow purchasing to buy smarter and marketing and sales to sell at higher margins. This would make this ISVs solution much more competitive.

Everyone is trying to bring in analytics to their product because they’re realizing there is a lot of great data out there! ISVs want to know how they can use it to make their businesses more competitive.

Some have tried to add predictive analysis to their own products. They added some nice dashboards, but not actual predictive software. Then, ISVs typically hire a couple of developers who know Python and can-do regressions.

And here’s where ISVs get stuck.

ISVs can do the data science, but have trouble connecting it to a useful reason to do the data science.

They don’t know how to communicate how predictive analysis directly relates to …

… more sales and better costing

… more conversions

… better ROI

… educating the sales and purchasing teams

It is traditionally difficult for ISVs to help their clients implement their strategy because they struggle to prove the effectiveness of how to best use that data! ISVs have the technology focus but are missing the business process application and where the information needs to be applied within the business process.

To quote Josh Wills, a Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.

There is a lot more to it.

Data scientists need to know the Minimally Viable Product (MVP). I.e. Here’s what you need to have. Here’s what your customers expect.

That’s where Collaborative Metrix steps in…

We offer 3rd party business insights and utilize a market survey of customers and non-customers, defining the MVP. The MVP may require a “gap-analysis” to see where businesses need to be in the market and where they may have holes in their predictive analysis.

We work to make marketing messages for prospects: “Here is this new AI model.”

For an example we will ask the question: “Do your salespeople need to talk to different people than they have been for the past 10 years?”

Let me repeat, we often find that the ISV failure is being too technically focused while missing the need to integrate their wide-range of knowledge and activities to the business process side of things.

What ISVs need…

ISVs have the skills, but not the business reasons for why.

ISVs need the ability to take the data science and transfer it to operations, sales and marketing.

It you would like to know more, contact us or go to our contact page and leave us a message so we can help you become more competitive.

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