This blog commences with the SEVEN types of Go2Cab Advanced Business Analytics. The five actions that are essential for the implementation of a successful business transformation follows the list of Go2Cab offerings in the space of advanced business analytics. The context of this blog is at a point in time beyond the construction of the business Target Operating Model where several important elements are well-defined. Such elements include the identification of your ultimate Customer, the Value Chain, required Services, and, Business Capabilities required to deliver the Services where the outcome of one or more Service will “Add Value” which, by design, will address one or more Customer needs.
Go2Cab shares its hands-on experience to draw your attention to simple actions you may wish to consider when dealing with Business Analytics whether in general or, specific to digital reform and business transformation.
Business Analytics Go2Cab Offerings:
Go2Cab can help you make sense of your data to ensure that the outcome is actionable intelligently. We do offer business analytics in SEVEN significant areas applicable to various industries such as Cloud, Transport, Portfolio and Project Management, Software Engineering, Digital Transformation, Mining, Food, Safety, Health, Education and Defence- to name a few. The seven major areas include:
- Numerical Business Analytics is when your data is numbers like time to complete a task, your weight loss per day, tonnes of freight or material hauled from origin to destination, time to clear an incident or close a ticket in a call centre environment, journey travel time and so on.
- Categorical Business Analytics is when your data is judgmental or opinion based like data collected via surveys where you answer questions with a selection from “Excellent” to “Very Poor” or from “Very High” to “Very Low”. Another form of answers is a selection of a colour. For example, “Red” may represent very “High Risk” or “Very Dangerous” and “Green” may represent “Very Low Risk” or “Very Safe” where other colours like “Yellow” and “Orange” are in between the “Red” and “Green”. Categorical data is frequently used in surveys whether in food, health or any service provided by an organisation where the organisation seeks feedback from the Customer.
- Text Business Analytics is when your data represent textual reports, feedback, review of reports or responses on project proposals. Another form of text business analytics applies to feedback or comments made by people via social media like Twitter, LinkedIn or Facebook. Go2Cab will help you analyse the text from hundreds of professionally accessed feed in a short time so that you get the insight and then make timely decisions on the next action.
- Video and Audio Business Analytics for any purpose whether analysis of media clips posted on social media channels like Youtube or, the analysis required for footage from a surveillance video or audio feed in industries like surveillance, safety, security or any operational environment where timely, relevant and accurate preventative measures are required.
- Mixed Business Analytics where methods used to analyse each type of analytics listed above are different. There are specific algorithms that best fit the data and the intended purpose and use of the outcome. Go2Cab can analyse situations where your data is a mix of the categories listed above to ensure that the result of the analysis is actionable pragmatically.
- Predictive Business Analytics where in most cases, the knowledge about something inadvertently went “wrong” is tolerable. However, to achieve a continual sustainable operational excellence, undertaking predictive analytics is a “MUST HAVE”. The challenge is to make decisions on timing of the business analytics, the vital-few data, the type of business analytics and the actions required to ensure operational preventative measures. Go2Cab uses best industry practices to ensure that the outcome of the analysis is, at all times, accurate, relevant and timely before the “wrong” takes place.
- Forensic Business Analytics where you need to timely analyse complex situational awareness where multiple factors are concurrently chaining in time and, you want to predict the next best [ie, optimal] actions. Go2Cab can undertake the analysis of the complicated situations in near real-time including factors like the behaviour of people. Such circumstances exist in every day’s environment. For example, to achieve the optimal traffic diversions in transport, it is essential to predict and influence the behaviour of the traveller. Similar situations exist in planning for events like sports, exhibitions, visits of dignitary, security and surveillance. The prediction of the most probable activity is critical to ensuring the optimal allocation, resources planning and execution and, the safety of all people involved where decisions may have to change dynamically depending on real-time information and data feed.
Go2Cab recommends and, is prepared to assist you pragmatically to instil the following actions into your operational environment to ensure that the outcome of the business analytics has an immediate impact on the desired business transformation in a manner that is, at all times, Accurate, Relevant and Timely at the lowest possible cost. These actions include:
Action 1: State Measurable and Testable Objectives
Start with the identification of a few measurable and testable objectives that directly impact selected Customer needs. Validate such objectives against simple, yet effective, criteria to assess whether meeting such objectives will lead to a Customer being Delighted, Satisfied or, whether the Customer will consider your deliverables as a “Must Have”.
It is constructive to note the two keywords “measurable” and “testable”. The word “Measurable” incorporates important decisions about what type of data you need, how often you need it, margins for accuracy which, in turn, will impact the mechanisms used to gather such data. There are several other factors which Go2Cab will help you identify and control using sound scientific approach to make sure that such decisions are evidence-based.
On the other hand, the word “Testable” also incorporates several aspects that are well beyond the topic of how to test the expected outcome of the specific objective. Such aspects include specific measure relating to running the operation over time, the frequency and specificity of disseminating notifications, the timeliness and relevance of such notifications and any suggestive actions to retain, at all times, the optimal level of operation. To this end, Go2Cab uses a suite of commercial tools that will help you make such decisions which will impact the solution you acquire as well as the configuration of the solution to avoid over-engineering and subsequent over-spending.
Once you set the Customer objectives, you define the business objectives in a manner that is very similar to that used when making decisions on Customer objectives. The recommendations made above should help you start thinking in the right mindset. It is very important to encourage “challenging” the decisions. It is equally important to verify and validate each objective iteratively. The term “verify” and “validate” are two different things. “Verification” is more to do with making sure whether there is any apparent “missing” objective. In other words, you test the “Existence” or “Absence”. On the other hand, “validation” is more concerned with testing the outcome of the objective in “real-time” or “near-real-time”.
Go2Cab considers “validation” in the context of the Dynamics of the situations (i.e., the moving parts of the business). For example, one of the simple questions to consider in the space of “validation” is whether the Customer notices a specific feature of the product or specific aspect of the service. The other important aspect of “validation” is the sequence of the delivery of one or more outcome of service. The term “verification” test the “existence” regardless of the “order” of the outcome. Validation ensures that the sequence of the delivery is timely and relevant. A simple example is to walk into an elevator (or a lift) where the doors close before you hear the announcement “Going up”. A valid challenge is to test the timeliness of such announcement after closing the door given that the elevator starts moving within a half a second after the announcement.
Action 2: Avoid the Sole Reliance on Averaged Data, Simple Charts and Percentages
Assuming that the raw data is reasonably accurate, organisations tend to quickly present the “evidence” by averaging, calculating percentages and plotting various types of tally and chart. Such data may represent customer churn, proposed pricing for a product or service, time to respond to a call, time to discharge patients, number of incidents or time required to clear an incident or, sales figures and pipeline over a prescribed period. If your industry is into health and food, such data may relate to tasting new products or general feedback about a new product during a pre-launch event. If your industry is in Cloud-hosting, ISP, entertainment or utility services, such data may relate to downtime, churn, customer profiling, usage of cloud-drive or memory space or some processors “provisioned” for the customer.
It is very common to be influenced by the height of the bar in a bar chart or the size of the area of a pie chart. The first fact to consider is that the height of the bar (or size of the area) may be misleading you in making the next decision. The higher the bar (or bigger area), for example, does not necessarily mean things are going very well, or things are very bad depending on whether the bar is sales or number of defects in a product.
A percent of something is very similar. The small or large percentage does not mean that things are very good or very bad. One example to illustrate this fact is to report that 80% or customers are happy neither means that they have no complaints nor it means that the “80” is a high-enough score, hence, let us keep going and you hear the cheer in the room “keep up the good work”. Even if you are in 90% range, you are not better than a relatively low ranked airline when it comes to their baggage handling service (where the majority of bags gets lost or damaged in transit). Similarly, you deliver a service with several downtimes per week if you are an internet service provider or, have several thousand items returned every month because something went wrong. The first thing you have to do is to use the “right” evidence-based decision making to set the “BEST” percent you have to meet over time. Such percent, which GO2Cab calls it the measure for CONSISTENCY is calculated using methods other than simple Excel functions. When the raw data is analysed using the appropriate methods which also incorporate the pre-set objectives, then you will find that the 80% was misleading.
Action 3: Avoid Generalisation of Data and Simplistic Analysis
Majority of organisations are ill-advised when data gathering become the point of discussions. Use simple charts, averaging data and percentages with CAUTION. Such simplistic reporting can (if not will) mislead you. Originations make decisions on the type of data and mechanisms to gather such data based on an already GENERALISED topic such as Stakeholder Management, Communications, Tracking and alike. Numerous details are obfuscated when the majority of the so-called experts (or advisors) are clueless in the domain. It is too hard for them to deal with complex interactions of parameters. It is also difficult for them to quickly prepare a few more PowerPoint slides and try to communicate to the C-Level keeping it at “high-level”. It is ironic that such advisors get away with such engagements as if the C-Level is not capable of understanding the details. The trick is to present the right measures in a simple, timely way yet; the measures incorporate the INFLUENCE of the DETAILS, CONSISTENCY and the OPERATIONAL DYNAMICS of the business.
One of the consequences of doing it otherwise (e.g., the generalisation) is to make decisions that there is a need to compile a survey and of course, engage one of the survey providers who is trusted by the advisors. The compilation of the survey is via using a set of questions that are already in the archives of the survey provider. In most cases, the questions are so generic where the context of the domain and the purpose of the data gathering is almost lost. To make things worse, the tally of respondents and percentage are reported where one can almost guarantee that the next decision is a sub-optimal if not wrong. Most surveys deliver fake answers anyways. For example, relating to workload, no one will neither tell you they are overloaded or underloaded. The answer is around 70% to 80% to avoid additional challenges where later, the respondents have to answer undesirable questions. Similar behaviour is true when it comes to employee satisfaction. There is nothing wrong with conducting a survey. The trick is to design the survey using an evidence-based approach which Go2Cab calls Design Of Experiment (DOE). In this way, the data gathered is serving a particular purpose by “Design”, and fake answers are significantly reduced or eliminated.
Action 4: Incorporate Operational Dynamics (i.e. the moving parts of the Business)
The advancements made in technology have enabled numerous organisations to make better decisions at much lower cost. Those who are old enough to have used the early versions of Excel (known as Lotus 1-2-3) in the early ‘80s can tell the difference when using the recent versions of Excel (e.g. 2013 or 2016). That said, the advancements and rich features come at a cost. For example, consider the manufacturing technologies relating to fighter jets. The early versions of composite material used made it possible to camouflage fighter jets from enemy radar but made the jets more susceptible to radio interference because the original metal structure acted as a shield for avionics controlling various functionalities. Similarly, the recent versions of Excel have encouraged more people to export data off CRM or ERP tools and then author bespoke code to undertake analysis and generate reports.
One would have assumed that advancements in visualisation [business intelligence] tools like Tableau, Qlik and suite of tools from TIBCO (amongst many other equally respected vendors) would have significantly reduced the need to hire Data Scientists and VB coders delivering bespoke Excel (VB) code.
Regardless of which way you want to go, it is important to consider two (amongst some other) factors. Firstly, Excel has no notion of units. You can manipulate the numbers with sophisticated formula linking any cell to any other cell. Unless there is a violation of basic mathematical rules (eg divide by zero), Excel is happy to produce a number. The significance of this aspect exponentially increases with the complexity of the formula where the tracking units get lost.
The other important aspect is that Excel has no notion of time (ie dynamics). It is quite easy to assign columns representing months or quarters or percent in increments of 10 or 20 to cater for (say) growth or decline of something. Excel will not and cannot show the impact of business dynamics in time (ie, how various factors including Customer’s behaviour (or any other moving part of the business) will interact with each other over a period of interest in configurable timeslots). The said assigned columns where a formula is calculating something is ONLY a snapshot of one specific point in time. Excel produces snapshot (like a still camera) whereas you need a “video” showing you how things will shape up or down in time as you adjust various factors. It is the dynamics of the operational dynamics (ie, the data, analysis and reporting that are ACCURATE, RELEVANT AND TIMELY) which will make or break the organisation. By the time the C-Level or any MANAGEMENT level is aware of something went wrong, it is often too late to act.
Action 5: Avoid Premature Reporting
One natural, yet very disappointing, the outcome of generalisation of topics discussed during the information gathering and the rather heavy reliance on highly aggregated data and simplistic analysis is the too-fast-too-soon decisions on tools. The other reason for making premature decisions on the selection and configuration of one or more tools is to please the Senior level managers and executives quickly. Despite the rigours methods used for selection of the tools, trials and proofs-of-concept, the reality is that some vendor will convince the organisation that they have the best tool and the “out-of-the-box” slogan gets things going for a while until the honeymoon is over. Such unfortunate outcome is not the vendor’s fault. The root cause for such faulty outcome is the mechanism to gather and process the information leading to the generalisation, and the way data were compiled, analysed and presented missing the first crucial steps as explained above. Since almost all tools have some form of reporting capabilities (which is now sold more like “ANALYTICS”), within 6 to 12 months, the organisation would have customised numerous reports. After a typical period of one year, the organisation realises that nothing has changed regarding efficiency, an increase in profits or better serving the Customer. Further, the organisation realised that the so-called “Analytics” was no more than simple averaging, percent and simplistic calculations but fairly powerful visualisation of data with little or no “BUSINESS ANALYTICS”.
Examples of poor decisions in the context of Actions 5 can fill a dictionary-thick book. Reports and dashboards are showing daily or monthly satisfaction of call centre where the gauge never move a few ticks below the max. The reason is mainly that of the generalisation, and simplistic calculations, the score for “Answering the Customer call is 4.9, 4.92 or 4. 96 out of a total scale of 5 reported every week or every month. No one questions the fact that the score will NOT be much different over time when one averages 3000 or 2700 or 2800 data points (e.g., time to respond to Customer’s call). Further, no one questions what the number means to form an Operational Dynamics standpoint. In most cases, the averaged numbers are a measure from the time the phone rings to the time an operator lifts that handset (i.e. the call centre staff say: “Hi, my name is Joe, how can I help?”). One wonders if the Executives are aware of the fact that the dashboard is nothing to do with the FULFILLMENT of the Customer need. Such misleading reporting is “ALL GOOD” since everything is always GREEN which, Go2Cab calls “Watermelon Reporting; “all green from outside but red inside!” A member of staff answering the call in 10 seconds has very little to do whether the call centre has addressed the need of the Customer. The Customer may have been placed on “Hold” for another 5 to 10 minutes per call and, it possibly took 10 more calls over 3 days before the call centre managed to FULFIL the Customer need. The same is true when dealing with time to clear incidents reported per unit of time (be it a week, month or quarter) or sales growth or Customer churn.