Wednesday, November 30, 2016

Why process automation is the new black

There’s a lot of talk about process automation - why?
Process automation drives the success of every organization by ensuring the constant movement of workflow. It’s part of your everyday whether you realize it or not. Take your pay stub - the entire process of working out your salary, calculating tax deductions, adding benefits and direct debiting your pay into your account - is process automation hard at work.
 
So why is the granting sector still relying on Post-it notes and spreadsheets to track funding calls and payment schedules?
First, let's back up and explain what we mean by 'business process’. Every organization is driven by processes - even grantmaking. You may not use the term ‘process’, but look close enough and you’ll find a set of processes in everything you do - just think of how you manage grant applications. The question is - are your processes automated - and should they be?   
Why should grantmakers care?
Repetitive, manual tasks aren’t fun. They’re time consuming and cumbersome. That’s why organizations look to automation to simplify crusty processes in need of a good shake up.  
Process automation saves you time and ensures accuracy. It can be applied to any number of processes involving any number of people.

What’s more - automation lets us focus on more important things. By 2025, experts predict automation will take over a third of our roles - and interestingly, 55% of employees feel positively about that, according to a recent study by ADP.
When it comes down to it, a grants management system is really a process automation tool tailored to a grantmaker's key processes. Listening to grantmakers, they tell us that granting can sometimes seem less about impact, and more about staying on top of paper trails. With lots of moving parts, the core functions of managing applications has plenty of opportunities for automation - from tackling heavy admin tasks, to routing the right information to the right people at the right time.
An automated future
It’s only a matter of time before all foundations - with big purse strings and little ones - will be using some form of process automation tool. Never slow to spot efficiency-savings, the private sector has been replacing sluggish processes with automated end-to-end alternatives for years.
Ready for an automation makeover?   
Keep in mind that most great process automation solutions will give you the flexibility to streamline your process without having to adapt it to the tool you’re using. Flexibility is a key value that we hang our hat on at SmartSimple, and it’s something we’re (quietly) proud to brag about.
But don’t take our word for it - have a look at the 2016 ‘Consumer’s Guide to Grants Management Systems’ by Idealware for some independent advice. In it, we came out on top in terms of the flexibility we offer, and came second overall.
To review the findings in more detail, have a look at this infographic we created to summarize the results of the report.  

Friday, November 4, 2016

5 critical first steps to creating better granting outcomes


How do you know you’ve been making a difference with your granting initiatives? That’s what every grantmaker is asking or being asked by their donors, funders and boards. While it’s important to know what you’ve accomplished, it’s even more important to have a solid understanding of how to gather, organize, analyze and share data, in order to ensure your granting activities achieve impactful, measurable results; this is where predictive analytics comes into play.

Predictive analytics uses your data to paint a picture of what is likely to happen in the future. This gives you the insight to make better, more informed decisions; increasing your ability to create positive change. Large corporations, retail chains, marketing companies and even sports franchises have been using this process to successfully forecast outcomes for decades, and it can be an invaluable tool for grantmakers.

Any successful predictive analytics program starts with 5 key steps:

1. Develop a Business Understanding. Identify your current situation and use your organizational goals to create a project plan. This plan will help you decide what constitutes success and will provide you with direction in achieving that success.

2. Develop a Data Understanding. Like most granting organizations, you likely have a large amount of data that you’ve collected over the years. Understanding your datasets is critical in ensuring that you’re properly organizing them for future use.

3. Bucket your Data. Once you know what data you have, you can begin to group your data into different categories. This is an important step because your data buckets will reflect what you want to achieve with your project plan. There are 2 specific variables you need to consider for this type of analytics exercise:
  • Discrete variables, where no group of data is more important or valuable than any other, and
  • Ratio variables, where data can be assigned a rating that is measurable and puts it into a hierarchy (eg. A is better than B).

4. Explore your Data. Step 4 involves extracting the relevant data from your buckets so that  you can identify what will support your project plan and help achieve your goals. Remember, analytics is as much about using the right data as it is the actual collection of it.

5. Create the Data MODEL. The final step is to create a data MODEL. This is where you take a look at the datasets that may be causing some confusion around your results. Predictive analytics is only valuable to the extent that the data you’re using for analysis is the data you should be using to address the questions you’re looking to answer. This last step closes the loop on managing the integrity of your data. As the acronym MODEL suggests, there are 5 key items in the checklist that need to be reviewed:
  • Missing - is there any information that isn’t included?
  • Odd - the data may be correct but there’s a good possibility it’s not
  • Duplicate - are there records of a specific piece of data that appear more than once?
  • Erroneous - there is very clearly an error in the data
  • Logical Error - is there an identifiable error based on the rest of the data collected?


If you're serious about using predictive analytics as a tool and want more detail on where to begin, SmartSimple's Getting Started with Predictive Analytics; A Grantmakers Playbook is an ideal starting point. This valuable resource will get you on the right track to building an analytics program for your organization.