Analyzing data is the most reliable way to assess your business and make decisions. So the question is, why don’t all companies have data analytics? If they’re waiting for a magical moment in the future when they’ll suddenly be ready to do machine learning and predict the future, they might be waiting forever. You can’t go from 0 to 100 overnight in analytics. Becoming a data-driven, analytics-forward company is not a destination, but rather a journey – a winding road with blocks to overcome and rewarding milestones along the way.
The analytics journey can more accurately be broken down into several steps, which you work through as your analytics capabilities become more advanced:
1. No Analytics
2. Descriptive Analytics
3. Diagnostic Analytics
4. Predictive Analytics
5. Prescriptive Analytics
The road to maturing your analytics capabilities is a rewarding one once you get on it. To outsiders, it may seem like a challenge and not worth the investment. But anyone on the road will tell you – the reward of analytics is immediate! You’ll see it in your insights and when you make better informed business decisions.
So, how can you get started on the road to analytics maturity? Below are some of the necessary steps to get from Step 1 – No Analytics, to Step 2 – Descriptive Analytics.
Determine your stakeholders/sponsors
Depending on where you are in your organization, you will need a business stakeholder or sponsor to enable your analytics-ready efforts. Determining your stakeholder(s) or sponsor(s) and making a plan with them will ensure you have the support you need to get things done.
Your stakeholder/sponsor should be someone who can:
1. Understand the value of analytics as a long-term investment
2. Provide the necessary budget for costs related to analytics tools
3. Get you access to the data and people you need
4. Advocate for you with other leadership
With a business stakeholder/sponsor in your corner, making decisions and getting your hands on what you need will be so much easier!
Prepare your data
Data is the foundation of analytics, so to have a successful analytics journey, your foundation needs to be strong and reliable. This is perhaps the least exciting step in the process… who wants to be responsible for cleaning up and formatting their entire organization’s data? Trust us, we understand. As boring as it sounds, if this step is not done correctly, your entire analytics journey will be set up for failure – so give this step the necessary time and effort for your long-term journey to be successful.
But wait – what does preparing your data mean exactly? Here are a few essential steps that cannot be skipped:
1. Assess and improve data quality.
Identify, bad data – outliers, missing values and duplicates for starters. Bad data can also mean inaccuracies or inconsistencies that will skew your analytics. Once these issues are identified, you can improve your data quality by revising the data collection process, i.e., making certain fields required, implementing duplicate rules, etc.
2. Organize your data into data sets that make sense for your organization.
This ensures data sets are concise and not too large. This step also allows you to set up data security in your organization in a meaningful way – so the wrong people don’t end up with sensitive information.
3. Mask private/sensitive data.
This step is especially important for patient-related and financial data.
4. Identify essential data that isn’t being recorded (and start recording it).
Your analytics won’t be meaningful if you cannot report on the information everyone is interested in!
So often we’ll have clients who want to report on a certain key performance indicator (KPI) – for example, a B2C company wanting to know which demographics each of their products are most popular among. They’re selling products and missing out on this analytics opportunity, because they don’t have any fields recording basic customer demographics! Your data is as robust and detailed as you set it up to be. There are no rules stopping you from collecting the data you want – the more data you collect, the better your analytics capabilities.
Foster a data-driven culture
Not everyone in your organization understands the value of data and how it can benefit them in their role – so you might need to show them.
This is where you have to get creative! How do you convince a bunch of professionals, comfortable in their roles, that they could be doing their jobs better using data? You have to demonstrate the value of data to them, using use cases they can relate to.
Aside from demonstrating, here are a few practical measures you can take:
1. Ensure data accessibility.
Your users won’t get comfortable with data until they’re able to access data they need to perform their jobs. Once it’s in front of them in an organized and approachable form, exploring it won’t be challenging, and they might make some great discoveries without even meaning to!
2. Reinforce essential data analytics skills.
This can be as simple as having everyone do some training on Excel, to begin with. There are tons of online resources that promote analytics skill building – so take your pick! Until you equip your team with the necessary tools, your efforts to promote analytics will be useless.
Choose your tool
The analytics tool you use is largely based on your type of organization and what you do. If you’re already using Salesforce, you might opt for CRM Analytics. If you’re ready for other strong tools, explore other Enterprise options such as Tableau or Microsoft Power BI, for starters. And if you want to take it slow, start with MS Excel. There are so many options out there you’ll have to do some research!
Your data is ready, your leadership is bought in, and your organization is well equipped to analyze some data and gain new insights. Now is when the fun begins!
As mentioned above, you won’t be able to start making predictions and forecasting your business’s future overnight. It’s a process to get there, but every step of the process comes with its own rewards! The next step for an organization with no analytics, is to start building Descriptive Analytics (yes, step 2!). These are usually your traditional pie charts, bar charts, summary numbers, trend lines and aggregated data.
This type of analytics is basic, but actually quite interesting as well. Descriptive analytics can tell you so much about your company’s performance – things you might have thought you knew! These analytics answer the question of “what happened?” or “what is happening?” When you know the state of your company, you can make decisions accordingly.
For example, descriptive analytics can tell a B2C construction company that Product A takes way more time and materials, while bringing in less profit, than Product B, which has a lower cost. This information alone is enough for the company to prioritize selling Product B and see an immediate increase in profits.
If you’re not sure how to get started in preparing your data and starting the analytics, bring in some experts to help! The missed insights and potential growth an expert may uncover is well worth it, and you’ll see the return on your investment in no time.
As your capabilities advance, you’ll get to step 3, Diagnostic Analytics, which tell you the “why” behind your data, and give you the chance to change what you need to and improve your business.