In a recent post, we spoke about the dilemma of needing insights to move beyond uncertainty, but told that the BI team is off-limits to the rest of the business, swamped by ‘mission critical’ requests.
So how do you discover which areas to improve or invest in when Finance and BI teams are overwhelmed with request after request?
Broadly speaking, there are three ways to discover insights:
- The traditional ‘get a ticket and wait in the queue’ approach, relying largely on others (and large budgets) to discover insights.
- The ‘export the data into Excel and do-it-yourself’ approach, relying largely on your own ability to discover insights.
- The ‘let the machine automatically analyse the data (from infinite angles) in seconds’ approach, relying largely on the power of AI to automate the process of discovering insights.
In most organisations, options (1) and (2) are the norm. However, in times of a recession, option (3) is critical to service the company to inform tough decisions today.
Option 1 - ‘Get a ticket and wait in the queue’
You have a problem, for example, you know sales are down. You have to dig deeper, but your Tableau or Power BI dashboards don’t tell you very much.
So what do you do?
Find an analyst in the team that can do the analysis for you? But in reality, this is a luxury most teams don’t have in good, let alone bad times.
Find a research agency or consulting firm to do the analysis for you? But in reality, this is a luxury that few ever have, especially during a recession when there’s freeze on all agency/consultancy spending.
Get a ticket and wait for the BI or insights team to prioritise your request? But in reality, you’ll be waiting a very long time for your team’s request to be looked at, let alone actioned.
Option 2 - ‘Export the data into Excel and do-it-yourself’
Most organisations want to empower their teams to self-serve insights. Hence the explosion of Tableau and Power BI dashboards. But the mere access to dashboards doesn’t say anything about the quality of the information they actually provide.
So, what does self-service insights in a typical organisation look like?
The end result?
While you end up with insights relevant to your business question, the entire process is:
- Fiddly - “Knowing how to select the right data, use pivot tables, remembering what filters to apply; it’s easy to make mistakes”
- Time consuming - “It takes me days to get this done”
- Prone to mistakes and human error - “What QA process? Nobody has time to review my analysis”
- Unenjoyable - “I would rather be spending time with my customers, not building reports”
- Not scalable - “what’s the VLookup formula again? I forget this every time!”
- Only as good as the questions asked - “How do I know if I’m asking the right questions of the data?”
- Limited by capability - “I can only analyse what I know how to do in Excel, e.g. filtering the data.”
The above list is not an exaggeration, it’s a representation of hundreds of comments when asked to describe their process of discovering insights. In fact, addressing this very problem was one of the key motivations for building Hyper Anna.
Option 3 - ‘Let the machine automatically analyse the data (from infinite angles) in seconds’
AKA: Discover insights automatically (at scale) with Hyper Anna.
Hyper Anna is an AI-powered data analyst. She proactively highlights anomalies and potential red flags that you didn’t think to look into, and helps to provide greater visibility of areas of the business that can become more efficient to identify cost cutting quickly and without overhead.
So, what does self-service insights with Anna look like?
Hyper Anna connects directly to your organisation’s databases in minutes. In the time it takes to connect your data to Hyper Anna, you’ll have:
- Bespoke insights, instantly - Automated the process of a BI specialist building a bespoke dashboard - something that would have taken months for a BI specialist to build - will now be instant. The entire process to discover insights takes minutes, not days, weeks or months.
- Actionable insights - Automating the process of a consultant to tell ‘you what caused this’ - something that would have taken weeks, $$$ and long powerpoint decks, it now takes minutes to have a clear picture of the business and what caused this, helping immediately shift into a ‘how can we act now?’ mindset.
- Relevant - Insights are relevant to me. I can ask ad hoc questions, but also have a clear picture of the broader context without being biased by what I know or am constrained to look for.
- Ease of use - It’s easy to use, not fiddly like using Excel. Explore and navigate your data with ease, whether you want a broad overview or specific details.
- Proactive - Replaced the need for analysts to continually look for ‘needles in a haystack’ as Anna automatically scans all angles of your KPIs and proactively shares insights with you. Further, Anna anticipates follow-up questions, allowing you to get deeper insights from angles you might not have thought to look into.
- Smart - Anna leverages advanced analytics, AI, and machine learning throughout the end to end process of data contextualisation, natural language processing, pattern analysis and guided journeys. This means the quality of insights are high, regardless of your technical background or training.
- Collaborative - Anna designs all charts and writes up all the insights for you, and makes it possible to share insights with your team and stakeholders instantly.
- Scalable - The only dependency holding up deploying Anna, is the organisation’s time to decide which databases and datasets to connect to Anna. Once that decision is made, it takes minutes to ingest the data. The result being, automated insights across the entire business, freeing the organisation from building manual dashboards or DIY Excel reports, preventing mistakes and human error.
Is this a plug for Hyper Anna?
Yes it is, but it’s also the very problem we’ve been solving for ASX and Fortune 500 companies for years, motivated by the reality that methods (1) and (2) of discovering insights (i.e. paying for insights, getting a ticket and waiting for others to do it for us, or attempting a DIY-job in Excel) are all pretty lousy ways of servicing the organisation for intelligence.
In a recession you’ll have to do more with less, however, this is a time where both the quality, cost and speed to insight matters more than ever.
So, that’s our thoughts for today. Good luck in your businesses. Stay tuned for more on how to find the key insights during these uncertain economic times.