Could Data Strategy Solve Some of Your Biggest Organizational Woes?
What is Data Strategy Compared to Business Strategy?
Strategy can be a loaded word - some of you roll your eyes when you hear it used in a business meeting (maybe not as bad as synergy, though). While we all talk about business strategies, strategy is often confused with tactics or plans. And, often, strategies aren’t followed or properly executed.
So, what is data strategy, and how can it help you solve some of the bigger organizational problems you may have as a digital business? It’s a long-term plan and practices that define processes, people, technology, and data usage within an organization. Strategy is the “how” we will do things and the continual practice we want to implement to get there. Strategy can’t be “checked off” a list, which is a good way to validate whether what you’ve created is truly a strategy.
For example, a bank may make the strategic decision not to collect certain data on their customers to remove bias from their marketing and other processes (or, likely and unfortunately, do the opposite), and a startup may make the strategic decision to not invest in any paid platforms for data and instead shift that money towards smart analysts and keep free tools until a certain amount of revenue.
Having an overall strategy for your data also means that you can focus efforts on projects with the best output for your business and know what resources you need (and don’t) to get the work done.
Why do I need a data strategy?
We talk a LOT about how important data is in the modern day - but we don’t talk much about how critical it is to have leaders in your company that understand data and can help you make strategic decisions with it that can help grow your company and mitigate risk.
It might sound strange to have a specific strategy for data only, but it can be a key item many businesses are missing as they move along in digital maturity.
You need data strategy because:
You could get sued if you don’t have clear strategies and plans in place for things like data privacy laws (like CCPA in the US)
Data quality can degrade if you don’t have plans to manage it - and your data is just as valuable as your other business assets
Your analytics teams will have high turnover (or you won’t have one at all) if you don’t plan for it
You will have higher tool and intelligence adoption when you have a strategy in place
It will be easier to justify and explain performance to investors or your board of directors when you have strong data quality and analysts
Clever analysis can highlight opportunities that you might not have seen otherwise
And, Data can help you improve profitability, customer experience, brand reputation, and more
If, as a leader, you’ve ever been frustrated because you can’t quite answer how well your marketing is doing, why employees keep leaving, or why you aren’t hitting your sales goals, the answer could partially lie in your data and your data strategy. These pain points typically mean it's time to focus more on data within your organization - by giving data leaders a seat at the table for senior leadership and establishing a full data strategy plan.
Just like other elements of business, what strategy is correct for your business depends on your industry. A bank or insurance business will need to take a different approach to data than an eCommerce company.
How Do I Know If We Have A Data Strategy Currently?
The first place to look in your organization to understand if you have committed to a specific data strategy is to ask your director of analytics or CDO if you have one. If you don't have one of these roles in-house and you're spending over $5M on marketing, it’s time to look to your analytics team to support your spending.
If you’re a director of marketing, engagement, etc., and you aren’t aware of your data strategy, it’s also likely that you don’t have one, or it’s time to review the old strategies.
The Steps of a Solid Data Strategy (In Order of Importance)
1. Executive buy-in
We put this first because even though many of us wouldn’t like to admit it, there is a political side to any changes within big companies. If the executive team doesn’t see the value, you must sell it to them first. Since evaluating your current strategy and putting it in place, a new one can change org structure, tool choices, processes, and ways of working - you need to be able to start from the top and have their voice behind you to make sure you can get all of those things done.
(You’re welcome to use our list above as some reasons to present to them the importance of data strategy)
2. Informed by the business strategy first
If you’re a bank and you adopt the data strategy of a lead generation company, you’re going to have problems (legal problems, most likely). If you’re a lead generation company and you adopt the data strategy of a major healthcare institution, you may go out of business.
So while we would all like to use the most advanced technologies and have a team of the brightest data scientists at our disposal, we need to be realistic of the needs of our customers and the industry - which means aligning our strategies to the industry.
Here are some of the ways that the data strategy needs to align to the business strategy:
Correct for the industry you operate in
Fits the growth goals of the business - are you looking to expand? Or is the business looking to optimize? The answer drastically changes what will happen from a data perspective
The risk acceptance profile of your company and legal teams
Your countries and states of operation
How are current teams structured and the overall business intention moving forward (are you off-shoring teams or all-American?)
What is the overall vision of the company, and where do they want to go?
Some of our clients get surprised by how often we want the ear of their CMO or CEO - to us, it’s the first thing that comes to our mind when we are invited to support a company. We want to hear from the visionary themselves what their goals are so we can effectively translate that into our work.
(OK, maybe we’re talking about executive buy-in again too - that’s why it’s #1 on this list!)
Ok, now, if you’re certain you have the two key ingredients to making (and executing) a data strategy, read on!
3. Data Maturity & Analytics Needs Assessment
Now that you know where to go, you'll need to find the gaps within your organization that you need to cross to reach the goals.
Example of results from the Google Digital Maturity Benchmark
A digital/data maturity assessment gets into the processes, tools, literacy, and more of your current org to give you a snapshot of where you are vs where you could be.
The Google Digital Maturity Benchmark is a good place to start as long as your company is large enough - it does cover more aspects than data alone, but all are related. You can’t have excellent digital marketing performance without data.
Most data strategy firms will also have their own flavor of a digital or data maturity benchmark if you choose to work with one to craft your strategy as well.
Analytics Needs Assessment
An example of Insight Lime’s analytics needs assessment results
The Analytics needs assessment dives deeper into some of the practicalities of your organization's needs based on where you want to go. It includes reporting, team structures, data quality, optimization/analysis maturity, and more to give you a checklist of improvements that you can easily plan out on a timeline.
Bonus: If you don’t think you’re ready for this whole process, there are a few quick questions that, if you find the answer to, you can assess your organization and make valuable changes now.
The 90/10 rule (by Avinash Kaushik) How much are you spending on data and marketing tools? How much are you spending on analysts to look at that data? 90% of that spend should be on analysts and only 10% on tools. You can have the fanciest tools in the world, but if you don’t have the analytical minds to interpret that data, it’s all for naught. An easy fix is to choose analysts over tools in the next fiscal year, or if you’re currently not spending much on either, pick the analysts first.
Ask your CMO or CEO: What’s the one question that, if we could answer with our data, you would be ecstatic? - and then go and find the answer to that question relentlessly. Don’t let technological, people, or process barriers get in your way; build what you need to answer that one question.
Check how much time your current analytics team spends on reporting vs. analysis. If the reporting number is higher, flip it. Analysis that can be used to determine business direction is infinitely more important than building more reports (bonus: If anyone makes a stink about this change, implement analytics ON your reporting, or just turn it off without telling anyone first. You’ll be surprised how few people ask where it went and/or how few people are actually looking at the data)
4. Org Strategy
At Insight Lime - we put the people before the tools. Because you can do a lot more with the right people than you can with the right tools and not the right people, it’s true that sometimes after assessing data strategy, you’ll see the need to make some org chart changes, and that's absolutely ok.
While we’re a data company, we believe that a vast majority of company issues can come down to team structure.
Org strategy for data strategy includes looking at:
Analytics team structures
Data literacy (and advocacy) across the org
Digital team structure
Scale of teams
Processes and distribution of work
We’re looking to respond to issues such as the lack of usefulness of analytics team outputs by examining the way that the analytics team serves other teams - as well as understanding what training gaps there are for the org as a whole and what interactions between digital teams may be causing conflict where there should be collaboration instead.
5. Data Governance
Depending on the business type, this step could end up higher on the list. Still, data governance is a major part of data strategy for risk mitigation and knowledge management. Without clear governance, you can both have potential legal consequences and have your work completely halt if a key person leaves with organizational knowledge that wasn’t properly documented.
Areas covered:
Evaluating laws in your areas of operation about data privacy and auditing current company compliance
Identifying gaps in knowledge repositories, knowledge management processes
Collaborating with security teams to identify any access management opportunities/issues
Establish data collection policies based on what is legal in your area, and based on anticipated changes to laws
6. Technology
The last (and still important) of this list is technology and data architecture. There is a LOT that even bigger organizations can do with free tools or very minimal spending on tools. Google Analytics and other digital analytics tools are free until you hit certain traffic volumes, and most data storage is also still affordable. If you only had a strongly implemented GA 360 instance, a database connected to it, and a slew of gifted analysts, you’d be better off than someone else with no analysts and a bunch of shiny tools.
We feel so strongly about this that if you do a tech stack assessment + people assessment and find that you are overspending on tools and don’t have the budget to hire more people - we challenge you to scrap some of those tools and pivot that money to people.
Tech stack & architecture auditing includes:
Assessing all departments to identify duplicate functionalities or duplicate tools
Right-sizing contracts and giving a full overview of the current spending on tools
Evaluating any gaps in technology
Identifying any pipeline issues that are causing a barrier to impactful analysis
Evaluating processes and systems to ensure they support impactful analysis instead of impairing it
What You’ll End Up With
If you’re doing this process from start to finish, the final output is typically a comprehensive audit, report, and roadmap of proposed changes.
So doing a full assessment is only the first step - some action items like improving processes and hiring new people take time. The way to be most successful with this is to prioritize realistically. If you want to be successful, we highly recommend having a project manager dedicated exclusively to the data strategy for the duration of the roadmap.
If you commit to using data strategically at your company, you will see outputs that will optimize your company, help you understand what truly drives your revenue, and have happier employees.
Sounds like a magic pill, right? Well, once you execute all of the steps above, it can be a step in the right direction to company growth magic!
(If you’re interested in learning more about Insight Lime’s data strategy packages or just have a question that you want answered for free, contact us)
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