How to Make an Airtight Case for Putting Business Intelligence in Your Budget

Big data makes business intelligence impossible to ignore

Only 33% of companies have set up a single enterprise-ready business intelligence and analytics solution, and many are using a “best fit” solution at most, rather than something that’s customized to their needs, according to a Gartner 2019 survey, “Business Value and Return on Data and Analytics Investments.” In January 2021, a Harvard Business Review Analytic Services survey saw that 88% of respondents were still using spreadsheets to analyze data, with only 33% indicating that they were highly satisfied with their tools’ ability to provide the intelligence they need.  

Purchasing and implementing a modern BI and data analytics solution to address this challenge can seem overwhelming and costly. However, neglecting to do so, or investing in the wrong platform for you, could prove even more expensive when you find that you can’t get any valuable intel from your data. Challenging though it may be, choosing a BI and analytics solution is becoming increasingly essential. This ebook sets out the key considerations when scoping out BI and analytics providers, and it outlines some of the most important factors for you to consider, so that you can effectively build your case for putting BI into your budget.

Is it time to invest in BI?

Let’s start at the beginning: Is now the right time for you to invest in a BI and analytics platform? It’s a big decision and a major investment. To present a watertight business case to your organization’s decision-makers for purchasing the right platform, you’ll need to ask the right questions. 

Answering the following five key questions will give you a clear indication if you need to invest in a new BI and analytics platform, and why it should be a priority in forthcoming budgeting. 

  1. Are you easily able to collect and combine data from many different data sources?
  2. Can you fully and easily access, visualize, and analyze this data?
  3. Are you sure your data is clean and accurate?
  4. Is your solution future-proof and capable of predictive analytics?
  5. Is actionable intelligence infused into your workflows, processes, applications, and products, so that using it is a natural and simple part of everyone’s work? 

Most companies we meet with answer “no” to at least one of the questions, and most are thinking about operational efficiency. For example, in its startup phase, a technology provider in the ride-hailing, delivery, and transportation space struggled with the perception of its brand and services as unsafe. Purchasing and implementing a BI and analytics platform enabled the company’s quality team to prioritize safety tickets and regularly advise team members how they could individually improve the quality of the experience they delivered to the user. Ultimately, the BI and analytics generated insights that offered custom coaching, which improved the safety and quality of service for all end users.

Another big blocker is how well all employees are enabled with data, and therefore how well it is adopted by end users. We know that embedding analytics into workflows enables all employees to make faster and more efficient decisions with data, thus driving adoption and greater ROI.

Presently, however, this isn’t happening in many organizations. In the 2021 Harvard Business Review Analytic Services survey, 17% of respondents say data analytics are built into few or no workflows, and 35% say analytics are in less than half but not zero workflows. That’s over 50% of companies with either little or no infused analytics. Furthermore, 69% of employees outside of IT/data teams must still exit their existing workflows to access the data they need, either by using a separate tool or dashboard (51%) or by requesting it from the IT/data team (18%), hurting productivity and performance. These needs can all be addressed with new, infused analytics, offsetting or even exceeding the expense of BI with improved productivity and performance.

Choose the right analytics rollout for you

There’s more than one way to approach a BI rollout and employee/company involvement, and each of the different alternatives will incur separate costs and services. Obviously, a bigger launch will require a longer preparation time and a larger spend commensurate with project size, so calculating the value of this, and the expected ROI, is recommended.

  • The phased approach: [Lower cost, slower rollout, slower ROI.] BI systems are launched department by department until the entire company has access. Often the preferred and recommended method, this may extend to client access as well. See department dashboards as an example.
  • Immediate implementation company-wide: [Higher cost, faster rollout, potentially faster ROI.] If time is a factor, or if your company is in dire need of BI across the board and wants to implement an effective BI solution quickly, it can be rolled out immediately across the entire company. This can carry more risk of not achieving complete implementation, thorough adoption or as noteworthy a ROI, and some prioritization is recommended.
  • Executive dashboards: [Lower cost, faster rollout, uncertain ROI.] The BI project is limited to those at the C-level to offer a real-time and big-picture look at how the company is performing.
  • OEM, embedding, and white-labeling: OEM, embedding, and white-labeling: [Faster rollout, uncertain cost and ROI, depending on solution.] Analytics functionality is added to your software offering in the form of embedded analytics, expanding functionality, increasing stickiness, and providing new revenue opportunities. Original equipment manufacturer (OEM) customers are also measuring ROI in terms of  new customer acquisition, as our research shows. In a 2021 Sisense survey of over 200 technology and business leaders, 30% of our customers reported they focus on acquiring new customers while 26% said they focus on growing their customer base. Additionally, 44% of prospects reported that they, too, focused on new customer acquisition above all. This provides a compelling case for the stickiness and expanded functionality that an analytics platform provider can offer over an in-house solution.
  • Clients only: [Faster rollout, lower cost, uncertain ROI.] Only end users are provided with BI tools to perform self-service reporting and provide your business the opportunity to illustrate key performance indicators and individual successes to clients.

Are you looking for internal and external (product) uses for analytics?

Embedding analytics into your products, and providing them to customers as white-labeled analytics, adds a new set of benefits to your company’s offering. It’s an opportunity for you to use data to drive revenue by creating analytic apps that your customers will want to sign up for. Deploying analytics products and services in this way enables you to stand out in your market by differentiating your products, expand your opportunities within your existing customer base, tackle new value propositions, and create a compelling way for them to get value from your data.

Embedded analytics also maximize your product’s stickiness and improve customer satisfaction and retention by empowering users to explore their data and discover insights on their own, with low or no code necessary.  

Factors that will impact a budget for embedded analytics: 

  • Size of customer/user base
  • Customization requirements
  • Costs per query
  • Licencing and security requirements
  • Support requirements (marketing, sales enablement, client onboarding) 

The decision to embed analytics can prove game-changing. Let’s consider a customer that operates in a saturated and high-churn market. Embedding analytics into the customer’s Salesforce software improves retention, because it ensures that the team can provide a higher level of service to its customers, before they report dissatisfaction and interest in a lower-cost competitor. Additionally, proscriptive usage data can be embedded into their platform to improve customer experience at scale.

Achieving evolution like this requires some spend, so it’s important to establish what you need to invest in and whether your ROI will exceed it. Establishing this will identify what you need to include in your business intelligence budget for embedded analytics.

Knowing whom to talk to: Speak to lines of business, not IT

It’s natural to assume that any budget for data and analytics will come from IT, but that’s not necessarily the best place to start when seeking and allocating money to spend on an analytics platform. 

Gartner’s 2020 survey “The Rise of Business-Domain-Led Data & Analytics” indicates that lines of business (LOBs) will be the primary driver of analytics adoption, rather than IT. The survey shows that business domains are bigger spenders on data and analytics than IT. 

Furthermore, Gartner concludes that most data maturity and market growth will come from LOBs, not only because they have more budget, but also because they have more users and can drive BI investment with their clear access to ROI and mission-critical priorities. 

To capture adoption, Gartner recommends data and line of business collaboration to democratize content creation, infuse complex data and multi-tool BI portfolios into business workflows to build actionable apps, and constantly iterate through innovation, differentiation, and standard reporting. These are features you should look for in your analytics provider and differentiators that we take very seriously at Sisense, where we strive to deliver next-level functionality that empowers users of all skill levels with the actionable intelligence they need to make better decisions and evolve businesses.

Knowing what to say: Creating the vision and the rationale to capture budget

Now it’s time to make the case for investing in data and analytics solutions. It turns out many CDOs struggle to do so, which means that data and analytics leaders must step up and start making the case for the measurable value of data and analytics to their stakeholders.

But how can they do this?

The answer is for data leaders to build a compelling ROI narrative with lines of business. This involves:

  • Working with business stakeholders to identify, prioritize, and select data and analytics value propositions
  • Assuring these stakeholders that investments in data and analytics are aligned to mission-critical business priorities and strategic business focus while delivering the highest net business value
  • Identifying the capability gaps that must be closed to ensure success

Having done the above, you are in a better position to build and sell a narrative about why a budget for BI and analytics is essential. With this knowledge, you can:

  • Create value propositions for data and analytics by mapping mission-critical business priorities to data and analytics options
  • Rank the business value of each of these priorities by weighing the business and financial benefits against your ability to deliver, including the data, analytics and technology, organizational infrastructure, and go-to-market capabilities necessary for success 
  • Identify the optimal data and analytics combinations that offer the best business value for your strategic targets and for a given investment level
  • Leverage the insights you get from your consultation with stakeholders to set priorities for your strategy and as critical input to your operating model and communications plan

Together, these target the desired business value — over and above the IT benefits— fill any capability deficit, and articulate the value of buying BI and analytics in a way that engages other business leaders.

Planning and selling an effective timeline

The last vital consideration is how long it will take for your BI project to be implemented. Of course, the scope of the project will impact timelines quite a bit, but assuming you’re rolling out company-wide, it’s quite typical for implementation to take up to six months.

When you factor in time to evaluate vendors, conduct proof of concepts, and implement the product you’ve chosen, a timeline of 3-6 months is reasonable and provides enough time to complete a thorough evaluation and implement a speedy resolution to your problems. For most prospective customers, their main concern is with implementation time rather than evaluation time, so it may be valuable to set an aggressive timetable. While stringing together open source tools in the form of an in-house build may seem faster, when you account for maintenance time and the overall functionality of such a solution, the choice of buying-in a dedicated BI solution becomes a more attractive and prudent proposition. 

Start building your BI plan now

Procrastination is opportunity’s assassin. The cost of not using your data to uncover new insights and measure performance grows every day, expressed as lower retention rates, diminished profits, decision delays, and added staff time spent on developing alternative solutions.

How valuable would it be to improve net retention, profits, or company efficiencies by 15% now rather than a year from now? That’s why there’s no time like the present to budget for BI, so you can immediately implement the means to create more success and drive growth, by infusing your organization with data and analytics. 

Gartner predicts that by 2023, 60% of organizations will combine components from three or more analytics solutions to build business applications infused with analytics that connect insights to actions.

If you want to accelerate down the road to success, launch a BI project using Sisense infused analytics now, and start looking at your data, and your future, in a whole new light.