The 5 rules of using data to make better decisions to achieve your specific business goals

Data is the root of all decision making

Rule # 1: Get high quality data.
Notice that I didn’t say use high quality data, but get high quality data. Many a product, brand and business owner are flying blind on past and current performance and even if they have data they’re outdated, inaccurate, thus making them irrelevant and useless. Getting high quality data involves first getting it from trusted sources. Paid research companies such as Euromonitor have been raking it in over the decades because of the lack of trusted sources. Today we have the internet as a source of getting free public data on the macro level which makes Euromonitor, who charges exorbitant fees, less attractive.

Public data from free sources such as FT, Businessweek, Wall Street Journal and even your local newspaper surprisingly get accurate data because they actually interview the owners of these data. But even these so called trusted and expensive data collectors have been found to present inaccurate data from my experience. So if you really want to get high quality data, you need to get straight to the source, like the publications I mentioned above. Once I had to present to the president of my company, the total market share of Debit volume in South East Asia and what I did was called my bank clients directly to get an estimate of the number of cards and spend per card to arrive at each of the banks’ volumes. It took a while (2 weeks) but it was well worth the time investment because no one can refute the quality of your data when you yourself got them straight from the owners of the businesses. It also results in a calming and confident effect in yourself knowing from where and who gave the data, which gives a stable bedrock to whatever you’re presenting. Thus, data quality means getting it raw and unadulterated from personally known entities and close colleagues and customers. This leads to the second aspect of data quality – the owners of the raw data. The best source are primary sources and most specifically, the owners of the data with which their own personal KPIs depend on. This means that your personal known sources’ own performance ratings are dependent on this data they’re giving you. From experience these are the product managers, general managers, CFOs and business owners whose salaries and bonuses depend on the quality of their KPIs which is measured by hard numbers such as number of units sold, number of subscribers and the like. Speak to them, and you’ll know when you’re talking to the right people when they have a daily or weekly metrics they monitor on a regular basis and are able to answer in a matter of seconds which means the data is important to them.

Rule # 2 – Ask the question – what problem am I solving?
Data is neutral. It’s like painting – value is extracted based on one’s personal interpretation of it. Unless it solves a personal problem, it’s useless as trying to book for UberBlack on a morning rush hour. So one needs to know what problem are you solving? Low sales? Low income? Declining sales? Pick one and you got to ask the key question – is this the main problem or is it something else? Pick one at a time and focus to solve it.

Say the problem is declining sales, what I do I first is check out the trend. How has it been for the past week, month and year? Has it been low to start with or was there a time when it was at a satisfactory level. If yes, what happened? There must be some variable that changed that led to declining sales. Check out the items, has there been a dip in particular items over same timeframe? How about particular days of the week? You may find YoY or Week on Week sales on a certain days have plummeted. Establishments are usually strong on weekends simply because the working class don’t have work and use this time to spend their hard earned salaries. But a dip on certain weekends where sales are normally strong may indicate changing spending habits on a macro level or competition intensity. That’s when you validate these assumptions which leads us to Rule # 3. However, you won’t be able to come up with these hypotheses unless you ask what problem you’re solving. Another technique is to check for outliers. Are there particular days that sales were so low that it brought down the whole month or week? Were there weeks or months that brought down the whole year? Maybe there were holidays or special long weekends where people opted to go out of town or do a staycation which led to a plummet in sales. Maybe there was a day where your supplier failed to deliver a whole day’s inventory so you couldn’t sell your top selling items. Whatever case it may be, outliers indicate a major cause of disruption in which case you can easily check your hypotheses against other data such as holiday schedules, special plane ticket sales, or great hotel offers.

Rule # 3 – Create hypotheses as you look at the trends.
As you go along, looking at graphs and tables, write down on a piece of paper what may cause these trends to happen. In the example of the declining sales above, I just thought of these possible causes for declining trends and single day sales plummets. There may be a lot but the more causes you can think of, the better so you can eliminate all possible causes and get closer to having a correct conclusion. There’s a bit of a catch here though. I believe that being able to have an instinct to see trends and patterns just by looking at raw data takes time to learn and a lot of practice. Like looking at a painting, nuances and discernment for personal and communal beauty and meaning may not come naturally for most people. Similarly, being able to have a mindset of automatically making logical and sound meaning out of data requires a lot of data and wrong interpretation of it before you get it right. So the challenge is to get out there learn by trial and error through school or a mentor. In my experience, it took a lot of case studies in business school and the hard reality of harsh criticism in the workplace to be able to get to a level of an automaton. The fastest way, then for a beginner is to take courses on statistics and get familiarized with the case study method of learning. There are free online courses or if your really want to be the best, pay for them.

Rule # 4 – Act on the hypotheses by crafting specific goals (max 3)
Do yourself a favour and use this goal setting formula: “To attain ______ by doing ______ by ______ date”. Cut through the clutter by writing down your goals as above such as I want to reach $100k US sales per month by cutting down on pilferage by 50% from $ 20k US to $10k US by June 31, 2016. Then post this on your office or restaurant to remind yourself and your staff. Even the top Fortune 500 executives don’t set clear goals according to acclaimed management guru Stephen Covey. That because they get caught up in the “whirlwind” of the urgent and now which takes most of their attention on a daily basis. They don’t have the time to sit down and check their bearings and set for themselves clear goals. Now , so as you don’t get overwhelmed, choose up to 3 goals which will have the greatest impact to your business. Usually these are financial goals and sometimes they are strategic as well such as be the most cited restaurant in Singapore by December 31, 2016.

Rule # 5 – Execute and check back every day then iterate
Another discipline that needs to be instilled is focused monitoring and continuous iteration as you go along executing. Your goals and activities are living documents as you always need to be flexible in changing courses as you learn more thinks as you go along. Your goal does not change but your activities to reach that goal may change. For example, you realized that cutting down on pilferage can only contribute 50% of the sales improvement. Get back to your data and see which other metric may give you the other 50% – reduce marketing?

Data Tool: Restograph

At RESTOGRAPH, we help owners and managers make accurate and timely decisions that directly improve sales and income.

Real time dynamic dashboards that can be accessed via mobile phones allow data owners to monitor performance 27/7, giving them peace of mind and saves time and effort so that they can concentrate on building their business.

“Business owners should always ask: Am I personally going to make enough money out of this, or get a promotion?”
– Donald Farmer, Former Head of Business Intelligence, Microsoft

Value based strategy and analytics always first ask what does an activity do to sales and income. Otherwise, there is simply no point of doing this activity. And activity always follows good insighting from accurate and up-to-date data delivered when you need it.

Restograph simply allows you to do this by accessing real time sales, inventory, costs and income at every varied conceivable permutations available. You wan daily sales, its there on the dashboard. How about YoY sales and income growth? It’s there. Top selling items? Daily, weekly. How about all time? You bet. Check it out @ and drop a note and request for a demo.