3 Ways analytics is revolutionising ERP software and how we interact with it

February 13, 2019

How personalised would you expect your interaction with your ERP system to be?

Turns out, our operational apps can be more adaptable, more proactive, and more insightful that we've ever imagined.

Oracle NetSuite ran its SuiteConnect conference in Sydney this week. Paul Farrell, VP industry product marketing and Jason Maynard, SVP global field operations, shared some exciting ideas about the future of ERP.

ERP will adapt itself to how we use it

Paul showed their Intelligent Form Assist.

This enthusiastic helper identifies patterns in how I complete data entry forms, and then starts guessing what I will do to before I do it.

For example, it will:

  • Identify that I usually only complete four out of the nine fields on the page when I record a new client, and highlight those fields for me

  • Notice that I typically tick the GST-free box for certain types of suppliers, and pre-tick it for me

  • Figure out the logic I intuitively apply when deciding order priority and suggest the priorities as I would

These are not rules that someone created in the system. It is simply the system watching my on-screen behaviour, identifying patterns, and predicting what I will do next.

My favourite part is that it marks every action it takes, and shows a little tooltip that explains the rationale behind it. It will be interesting to see what it teaches users about the workings of their own intuitive decisions.

I love this new sense of elasticity in a system category that we traditionally perceived as rigid and heavy.

[caption id="attachment_14424" align="alignnone" width="1169"]

Netsuite's Form Assist suggests: You have set Order Priority of 1 to 84% of customers with industry Wholesale and Annual Revenue greater than $5M.[/caption]

ERP will identify, think and act faster than us

What Paul showed next, gave me the same feeling I had when I first experienced a sports car from the driver seat: right, now we have power, let's go!

As background, we looked at how "analytics latency" drives "reaction latency".

As a human:

  • It takes me time to know that there is a problem. Eg., a shipment is running late

  • Then it takes me time to understand why. Eg., that shipper has been slack recently

  • Next, I scramble around figuring out a solution

  • And finally, I need to actually go about fixing to the situation

So: Detect -> Analyse -> Decide -> Act.

Every step that requires a human, will take time.

Any step that can be automated will shorten our time to resolution and minimise the potential damage.

Paul showed a live demo (recorded, but real working system) of Netsuite's Predictive Risks page.

It showed that a certain shipment is at risk of being late. At risk, but not late yet. We are predicting a problem before it actually happened.

[caption id="attachment_14425" align="alignnone" width="424"]

Predictive risk: 78% chance of this shipment being late[/caption]It then goes on explaining (Analyse) that this is because 61% of the shipments by that shipper over the last week were late.

It then suggests a solution (Decide). The ERP should fulfil the order from another location from which 89% shipments arrived on time in the last week and it also has excess inventory.

[caption id="attachment_14426" align="alignnone" width="739"]

A one-time recommendation dynamically constructed by the ERP system[/caption]Finally, I can authorise the system to just go ahead and apply the fix. This saves me the hassle of updating orders across the system.

So we've seen the system convert 'identifying that we have a problem' to 'predicting that we are at risk of having a problem', explain the reasoning, suggest a solution, and carry it out.

The effect on reaction latency must be huge here. It turns the whole idea of reporting on its head. I don't want to review reports. I want this enormous computing power to analyse, predict and really think for me.

Big Brother, but in a good way

Consider the colossal amount of business data that Netsuite has access to.

More than 20 years of business data, across 40,000 Netsuite users plus access to (anonymised) Oracle data cloud.

That's a lot of data.

Data + machine learning = better business results. Oracle Netsuite has a group of savvy data scientists fine tuning a bunch of sophisticated algorithms to draw business potential out of data.

[caption id="attachment_14427" align="alignnone" width="1070"]

Netsuite has access to a vast amount of business data[/caption]Privacy concerns aside, there is a lot to be learned from such a treasure trove of a dataset.

NetSuite claims to be able to recommend business improvements and fine tuning, but more excitingly, opportunities for growth, based on machine learning algorithms analysing our business data, and the cohort of other businesses in our industry.

NetSuite can identify that one of its users is at a prime position to grow into a new market, optimise their pricing structure, or bring manufacturing in-house.

Speaking to Netsuite partners it seems that they still don't have access to this knowledge to make growth recommendations for their clients.

But assuming that the tools are being cut and sharpened now, the power of ERP systems for small business has just been supercharged, big time.

Disclosure: Inbal Rodnay Steinberg travelled to SuiteConnect in Sydney as a guest of Oracle Netsuite.

Tags
Analytics,ERP,machine learning,NetSuite

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