An “asset” is a resource that a business owns or controls with the expectation that it will provide future benefit. You and your data analyst colleagues likely invest energy, attention, and capital into creating and developing assets, and in return expect them to positively impact your business. Data is an asset, and this same expectation applies to it.

There are many different types of data assets. Here is how we categorize the most common ones:

1. Raw data - Customer behaviors, financial performance, etc.

2. Logic - ETL pipelines, tables, and datasets

3. Knowledge base - Business stakeholder-facing dashboards, reports, and analyses

Knowledge base assets have the most direct impact on business outcomes. And the further downstream we go, the more expensive an asset becomes (accumulated value). With this in mind, we are focusing today on this third category of data assets. Whenever we mention data assets in the context of this discussion, we will be referring to knowledge base, business stakeholder-facing assets that are developed by analysts. These assets may include the code used for querying and modeling, along with reports and dashboards created for business stakeholders.

As opposed to other standard business assets that depreciate (e.g., machines, equipment, etc.), data assets become more valuable when maintained and managed efficiently. This is because they can be utilized an infinite number of times, and can be further transformed into additional data assets.

If we don’t receive enough value from a given investment, the asset is likely disadvantageous and should be managed differently. The goal is to generate the highest return on investment (ROI) for your assets. Let’s take a deeper look into data asset ROI and the best methods for maximizing it.

The Data Asset’s ROI Equation

To find a data asset’s ROI the ROI of the data asset,  we need to measure its value (return) and cost (investment). A data asset’s value can be measured by the number of strategic insights it produces and how much it positively impacts the business. In order to generate insights, stakeholders must use and engage with the data asset. Thus, the more stakeholders engage with the data asset, the more valuable it is (this is probably why you hate ad-hoc tasks, and why, the last time you sent a static CSV export from your Tableau dashboard to a business stakeholder, something died inside of you).

On the investment side, there are three main costs associated with the data asset: infrastructure and software costs, the analyst’s capacity (or time investment) allocated to develop the data asset, and his or her salary.

Given our equation above, to maximize a data asset’s ROI, we would have to increase its value or decrease its costs. Unfortunately, we don’t always have control over these components. Salaries are fixed by the market, while the cost of the infrastructure and software we use are usually predetermined in agreements between your organizations and vendors (and there’s definitely a limit to how much caching we can do in order to reduce that BigQuery spend!). Thus, the main levers that data analysts can influence are the time allocated to develop the asset and how much your stakeholders engage with it.

Decreasing the Cost of Your Asset

We often find that data assets are requested (primarily by business stakeholders), created (primarily by analysts), used once, and siloed away. This cycle leads to repetitive work and a huge waste of time. We know this sounds cliché, but your time is worth a lot of money. To cut down on your time investment, it is important to make your development process more efficient.

The best way to do so is by repurposing previous work. We call this being an ADLT.

Making your existing assets accessible, well documented, easily located, and properly templatized will help when we (1) receive a task that your assets have already resolved and (2) need a similar asset to use as a base for creating a new one (by editing the code or report, changing filters, etc.). Trust us - this will save a tremendous amount of time and effort, and even save on infrastructure costs for the organization (brownie points!).

Increasing Your Asset’s Value

As we’ve already mentioned, there is no limit to the number of engagements your data assets can drive. By increasing engagement, we’re tapping into unrealized value that will significantly boost your ROI. This could have an immense impact on your organization, data operation, and your data operations’ perceived value within the organization.

The secret to increasing stakeholder engagement is treating your data assets like any other product or service your organizations create. Every product has a team that contributes to its success: a product manager, marketing manager, customer success and support specialist, and more. Try putting yourself in their shoes and manage your data assets in the same way that they manage their products. This will help you improve your data assets’ quality for your stakeholders, increase engagement with the assets, and get you the credit you and your work deserve! Here are some best practices that we can get started with:

Build and design your assets for your target audience

Who is going to use your data assets? How data-savvy are they? What tools do they use? What insights are they interested in? And what format of presentation would be the best for them? Interview your stakeholders to understand their needs, then build a product that fits them. Otherwise, they won’t use it. Using templates via Jira, Typeform, or Google Forms can help facilitate the process of properly capturing important answers. One of the best dashboards I’ve ever built (i.e., one that got tons of engagement) was designed based on the template of our company deck so business stakeholders felt good screenshotting and forwarding it to customers.

Make your assets easily approachable for your business stakeholders

Research where stakeholders spend their time, and locate the assets there. Document and organize assets as they are created so your business stakeholders can easily use them when needed. It’s crucial to promote these directories as the first touchpoint for this type of stakeholder. They should review existing assets before requesting the creation of something new. If companies don’t waste time building products that already exist, neither should you. And don’t forget to keep your assets up to date! If you build a stale repository of assets, no one will use it. If you’re giving your users the old yellow pages guide, don’t be surprised if they keep calling the wrong number.

Provide usage instructions and customer support

Make your data assets as user-friendly as possible (here’s a guide for doing so with dashboards), but also provide guidance on how to use them. This may include writing “how-to” instructions in Google Docs or creating FAQs from previously asked questions in Discourse or Stack Overflow. That way, when a question comes in from a stakeholder, you can automatically direct them here to find the support they need. From our experience, about 20-30% of incoming requests to analysts are about assets that business stakeholders are confused about how to use. What could you do with an extra 30% of your time?

Additionally, hosting proactive training sessions with business users or using a customer support system with platforms such as Wix Answers or Zendesk can put you ahead of the curve.

Monitor and analyze asset usage

Track the usage of your data assets to understand who is using them, when they’re using them, and how they are being used. Reviewing BI tool usage statistics and analyzing relevant query logs can be very informative. It will help you improve existing assets and make future assets more relevant to increase stakeholder engagement. Finally, removing existing assets that are no longer being used is a great way to free up bandwidth and reduce unnecessary clutter (as well as overall expenses).

Increase assets’ visibility and re-target users

A well-made data asset can impact a large part of the organization, which is why you should be marketing your assets’ beyond your immediate circle. A couple of effective approaches are to create a Slack channel for announcing new assets and to use Mailchimp-like email campaigns that send internal weekly newsletters promoting existing assets that are getting attention in the organization to relevant stakeholders. To help with your re-targeting process, you can create a spreadsheet and keep track of which topics your stakeholders care about. We can guarantee they will be delighted to find a valuable data asset before they know they need it.

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If you follow these practices, not only will your life at work dramatically improve, but you will also start receiving credit for what we’re doing. However, doing so isn’t necessarily easy. Analysts who want the highest ROI on their assets need to use the proper tools and streamlined work processes.

Developing and maintaining a well-oiled data operation machine can be much more chaotic than you’d think. Thankfully, some messy problems have elegant solutions. Rupert will help you reduce the cost of your assets, maximize their utilization, and clear your backlog. Want to give your data assets an ROI boost?