Risk Management at Scale Part 5: change management and automation

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{If you missed the first four chapters of Risk Management at Scale, read those first and then come back here}.

You did it!  You’ve determined what your qualitative vs. quantitative data points are, developed ways to collect all the data, analyzed the resulting information, and built a framework to consistently provide you with cues to your customer’s risk. You’re all done, right?  The answer is: almost. Creating the process, no matter how simple, is just the beginning. Now you have to automate as much of the intake as possible and make sure your team follows the full process consistently. This requires habit creation through change management.

Hopefully, you’ve done yourself a big favor by automating as much of the data collection, analysis and interpretation during the framework phase.  This will help reduce the weight of change on your team. Any of the data your platform can produce and deliver into your CRM tool (like Gainsight or Salesforce) will also ensure that there’s no delay when key performance metrics drop for your customers.  Additional steps you can take to automate your data collection and interpretation are as follows:

If a computer can do it, make sure a computer is doing it

Yes, people are great at doing things that are complex and can “kill two birds with one stone” by interpreting data as it is entered into the system.  BUT humans are also fairly unreliable, through no fault of their own. The best part about a computer is that it will do exactly what you tell it to exactly when you tell it to.  (The only time this is not the case is when the computer is being told more than one thing and the things it’s being told to do conflict, or something changed what the computer is being asked to do.  Really.)

Break it down to speed it up

If you can break your data process into steps that a computer can do and steps that a human has to do, you’re better off.  And if you feel like a human has to do all of it, you haven’t broken the steps down far enough.  How is the data getting out of the platform you’re extracting it from? Is a person logging in and downloading it?  Can you set up a job to deliver a file to a folder or inbox on a regular basis instead? Do that. How is the data getting into the platform you use to analyze it?  Again, if you can run a job with a computer to ingest the data automatically, do it. Don’t know how? I guarantee it is worth your time, money and collaborative efforts to enlist someone from your engineering team, data team or even an outside specialist to set this up for you.  The time saved and the reliability you buy are well worth the expense.

Use the tools you have, but use them better

Only using Excel and don’t have a CRM?  Using Zendesk and Salesforce, but they don’t talk to each other?  Have Gainsight for scorecards, but haven’t set up automated scores?  Don’t worry - use what you have, but take the time to automate and optimize it.  Build a macro in Excel to pull in information from a folder on your shared drive.  Use the API connections that your software has (like Zendesk and Salesforce) to automate the process of updating data back and forth. Build a field that Gainsight can leverage to track your scores automatically. Don’t know how to do these things? Google is your friend.  It’s very likely that all the software you’re using has some kind of help documentation on the world wide web. Carve out a few hours, roll up your search sleeves, and follow the step-by-step instructions on how to accomplish what you need to do. Trust me, it’s worth your time now to save time (and ensure accuracy) later.

Reduce the amount of work your team has to do

Simplify.  Building complex models and multiple data sets is great, but can you get the same or similar results with less?  To be clear - the automated stuff can be complex as long as it is valuable and truly automated. When it comes to the components that your team has to enter, interpret or act upon, simplicity is best.  Take a moment to look at the aspects of your process that people are going to have to update or interact with - are all of these points necessary? Are you sure? If you can simplify, even just for now, you’ll see greater success during change management.

Great!  You’ve automated all the tasks that can be automated.  You’ve connected your systems to talk to each other and you’ve set up jobs for your product to run, ensuring data is delivered in a consistent, timely manner.  Now take a look at all of the people-run parts of the process. Document the steps; be clear and concise. Use screenshots. Draw boxes and arrows to indicate exactly what you want done.  Now put this documentation in a single, easy-to-find place and use it to train the team on the process.

Training the team is just the first step in the change management process.  But telling your team how to do something and expecting them to do it is not enough.  They will continue to do things the way they have been unless you move them to do it the new way.  This means consistency, clarity, and (nearly) constant communication from you.  

People hate change and the way things are, in that order.

That means no matter how much better the process you’ve devised is, it is far easier for humans to follow their old habits.  Habits are our lazy brains’ way of being efficient. Once a habit loop is formed, the only way to break it is to form a new habit on the existing trigger.  

So how do you change a team of people to adopt your new process?  You follow up with them. A lot.

Here are the steps we take to change manage teams (see our future post on Change Management for details):

  1. Acknowledge that change is hard

  2. Explain why the change needs to be done and what the intention is

  3. Acknowledge that the process may not be perfect

  4. Request that the whole team try to only use the new process and not use old methods for tracking

  5. Ask for feedback, then act on it

  6. Create visibility and give kudos for successful change

  7. Provide dedicated time for team members to walk through the process again

  8. Bring up the new process and request feedback during team meetings

  9. If a team member is struggling to adopt the new process, sit with them on a regular basis to help them get on board

  10. Continue this for at least three months, or until it is clear that all of your team members are comfortably following the new process

The worst thing you can do is roll out a new process only to find out that no one is following it. Especially when it comes to risk management and health scores, you MUST have consistent and reliable data on your customers.  Getting your systems in order to automate as much of the process as possible is a necessary step in the journey to customer retention and risk management.  Ensuring that your team have formed excellent habits around maintaining health scores and following risk playbooks is the pivotal final step toward success with your customers.

As mentioned above, once a process is a habit, it will be nearly effortless to continue.  This leaves your customer team with more time to be strategic and thoughtful with your customers, leading not only to better, happier relationships, but stronger guarantees of renewal and expansion.

If you’ve found this blog series to be helpful, consider attending one of our Risk Management Seminars in San Francisco, CA.   More information is available on our website or at meetup.com

For more information about Risk Management, or to request a customized Risk Management Workshop for your team, send us a note at contact@sandpoint.io.

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