Intelligence is a term much abused by some, especially politicians when they talk about ‘intelligent solutions’. Intelligence is not even an adjective. It means ‘the ability to acquire and apply knowledge and skills’. This gets us closer to what Business Intelligence is actually about.
Politicians muddy the water again by mouthing on about military intelligence, which is snooping on our enemies and occasionally our friends.
All is fair in love, war, and business though. I will stick with my definition
‘Business Intelligence is gathering, synthesizing, and applying knowledge, and skills regarding our own, and our competitors’ business performance.
This article is about doing this with intelligence, using the simple roadmap I detail in bullet points further on.
Business Intelligence (BI) Is not the Same as Business Analytics
Business Analytics is all about crunching information, using big data mining and quantitative statistical analysis to predict the future. If the software is really smart, it might even propose intelligent solutions (that adjective again). The hole to drive a bus through is garbage-in-garbage-out. If we dump a sack of potatoes, some rotten, into a chipper we know what we are going to get.
Business Intelligence takes a more thoughtful look. It peers deeply into what happened in the past, what is happening in the present moment, and how we should prepare for the future too. First, it provides thought-provoking high-level data for perceptive leaders. Then, it relies on human intellect and brain power to decide what to do next. I know what number my money is on, because I am still trying to get my mind around self-driving cars.
There is, that said, a third alternative I rather like. This is where we take the best from both approaches. Once we have validated our Business Intelligence data, we can put it through the Business Analytics machine and see what comes up. This could produce alternative scenarios adding to the overall quality of the management decision.
The Ancient Romans had a god they called Janus. Janus was in charge of beginnings, gates, transitions, time, duality, doorways, passages, and endings. He was able to look behind, ahead, and to the left and right simultaneously. I would have more hope for the future if we had a bunch of Januses in charge of the nations. In the interim, we do have the torch of Business Intelligence to shine ahead.
We Already Have Boatloads of Data. What Happens Next?
You take a step back, and wonder whether you should stick a stun grenade in your server and start again. If you think carbon is a problem we ignored for far too long, just wait for data. Did you know 90% of the world’s data did not exist two years ago? You could be sitting on an incredibly rich lode of information. You just need to know how to pull out the nuggets, and this is what Business Intelligence is here to do.
Rule Number One: You Do Not Need the IT Department
Don’t get me wrong. I love IT to bits. I just think they tend to become stuck in the swamp tickling interesting alligators, instead of reaching insightful business decisions and taking action. IT has made its contribution in the case of Business Intelligence by developing fantastic software solutions. These come with dashboards that help leaders get to decision points sooner.
IT users are increasingly seizing control, and driving solutions out of Business Intelligence, of which we might not have dreamed five years ago. This trend is particularly evident in medium-size businesses with a depth of skills and a wide spread of user intelligence. The challenge is to harness this into a high-stepping team of winners.
Data Mining at the Heart of Business Intelligence Solutions
Data mining is a digital process aimed at discovering patterns in big business data, in order to yield an information structure business managers can understand, and use. For example, it could relate to bookings in different-size hotel suites by duration of stay, season, and age of the person making the reservation.
This is powerful medicine for holiday accommodation marketers, who now know when and where to hunt for leads. Here is a useful link to free open source data mining software to play with until you get the hang of it. I chose the word ‘play carefully, because data mining does not have to be a pain.
Key Stages of Implementing a Business Intelligence Solution
Find a Practical Solution:
There are loads of freemium and premium Business Intelligence packages on the web. As usual some are good, and some indifferent. Avoid going for one that claims you just jump in and drive. You have to set things up the way you want on the dashboard first. Make sure stakeholders understand.
Have a Standardized Approach:
BI is off to a bad start if each member of the team draws different reports. You can always change the settings later when you have a store of hindsight. Align the needs of different departments to a single cohesive data model. Use strategic foresight to anticipate the future.
Make a Training Investment:
Carve out time for participants – including yourself – to work through the onboard tutorials of your preferred Business Intelligence software. If your provider offers a half-day seminar for key role-players, accept it. When you are competent with the basics, you will have the confidence to explore further.
Commission your system and run your data:
You’ll find your ‘moment of truth’ exciting as you use your dashboard to produce high-level information you can use. You will find a mixture of highs and lows at this stage, but don’t let this get you down. You are doing this to find areas where you can improve.
How to Analyze Data Successfully
After you have sourced and set up your system, and trained your people, you are ready to commission it. Before I move on to that phase, let us briefly take a system view of data analysis, which is the core of what you have purchased. Business theory suggests there are four levels of this:
- Descriptive Analysis reveals the bare historic and current facts
- Diagnostic Analysis identifies reasons behind these events
- Prescriptive Analysis suggests actions based on the information
- Predictive Analysis forecasts the future to inform our decisions.
Let Us Take a Deeper Look at Predictive Analysis in Business Intelligence
This to my mind is where things come together, as our data report facts we can use to figure out what is likely to happen, and respond proactively to our advantage. The Math Marketing principles help explain the reasons behind a successful outcome, or stimulate ideas for resolving a problem.
Five Key Stages in the Process
These issues could range from falling website traffic to a mass emigration of customers. In fact, any business event should benefit from the light it shines. Here we focus on problems, although you can apply the theory to any business outcome.
- First, we get the facts so we can define exactly what happened. We box out the reasons at this stage, because we do not want to cloud our thinking. We are looking for correlations with other events (the reasons) so our main focus is what changed.
- Then, we start wondering what is happening, using creative-human, and machine-generated ideas. Is our content, for example increasing our bounce-rate, or has something slipped in the front office that is upsetting customers and turning them away.
- Next, we turn to understanding what is happening now. One of the greatest joys of business intelligence is it generates real-time live data. The action gets interesting as we change problems into solutions and see upticks develop. However, the final chapter could take weeks to come through.
- While this is happening, we shift gear from the past and the present to what might happen in the future. With high-level information at hand, we can foresee future possibilities and their causes. If these outcomes do occur later, we should already be ahead of the game.
- Finally, we do probability modelling to find out which of these possibilities are most likely to recur. Then we can develop risk-avoidance and recovery strategies, and build these into future products and plans. We are ahead of the wave and surfing the future.
Business Intelligence Should Make, not Cost Money
While it costs money to collect and store data, extracting intelligence should improve our bottom line. In February 2017, Forbes reported an uptick in Business Intelligence on a cloud. In a final act of independence from IT in the operational phase, 78% of companies were planning to increase their use of cloud for data management, while 46% preferred public cloud platforms for Business Intelligence analytics.
When we met, you had a pile of data but were short on ideas how to bottom out on what it said. I hope I have given you useful insights how to go about it. I close by reminding you what magician David Copperfield said. ‘Passion will keep you going when the going gets tough.’ Go well as you explore the world of Business Intelligence, and take action. Gathering intelligence and even analyzing and forecasting is useless, if your strategy does not evolve with it.