Communication Plan and Culture

Star Industries is a company that manufactures and markets windows in Western Australia. They are positioned at the high end of the market in an industry where most competitors bring in lower-priced windows from Asia, and Star trades on their premium branding and reputation. They have limited diversification, but sell throughout Australia, with manufacturing in WA and corporate headquarters in Sydney.

One of the biggest challenges for a small or medium-sized enterprise is to gather data. It is relatively easy to gather data from staff, because they are a captive audience. An app like Officevibe works fairly well in terms of asking staff a handful of questions per week about their views on the company and their jobs. Gathering data from clients is much harder. The response rate on client surveys is around 10-15% at best (Fryrear, 2015), which is usually not statistically significant. This means that the company is unlikely to work with anything other than anecdotal information. So a strategy should be in place to gather that -- ensure that all customer-facing personnel understand what information the organisation wants to get from its clients and that they should take advantage of contacts with clients to seek out that information.

2. Identifying business problems is tricky. You certainly want to have a clear, identifiable process for when a client comes to you with a problem. But ideally you also want a process whereby you can learn from clients about problems as well. A Client Action Committee or some other structure can provide a forum for the sort of open-ended client interactions that would yield information about business problems that may be less apparent. It is also worth checking up on where people talk about you online -- if your company has a Reddit you'll probably be able to read plenty of gripes.

3. Identifying information needed to solve a problem is a trickier matter. For this, the company needs to have a process of inquiries in place. Basically, the easiest problems to resolve are those with metrics, so if possible one should acquire those metrics. The best way to deal with this is by asking the customer. Use your CRM to find out what the customer is thinking -- in other words, how does the customer measure success because that is how you should measure success. You will never know if you do not ask, so use your tools to reach out, or talk to them in person, or have your reps talk to them when they contact you. Each customer interaction is an opportunity to learn how your customers define success.

4. Reliable information is tough, especially for smaller companies. You do the best with what you have at your disposal, recognizing that there is an ROI attached to finding out every piece of information.

5. Formal networks do not yield, by definition, yield information not held in formal systems. Informal networks by definition do. One of the better ideas for informal networks is actually to host events. These can be webinars, conferences, social gatherings -- it sort of depends on your customer base and their geographic dispersion. But you need to create those opportunities for interaction, as those are the informal networks on which you will rely for information.

6. It can be difficult to review knowledge not held in formal systems. The basic approach is probably just to get it into formal systems so that the knowledge becomes institutional, rather than leaving it in people's heads. There are basically two steps to this. First is documentation. This will be a theme here. If you have a documentation platform -- there are several, like IT Glue or something like that - you have a mean by which institutional knowledge can be recorded. But you also need a process for reviewing this knowledge. So within each division and unit you'll need to have a specific time frame for reviewing information that has been recorded. Recording information without setting aside time for review is almost pointless.

7. Testing information for reliability and validity is something that can be done at all stages. Research design is critical -- you know ahead of time what a reliable sample looks like, and what it will take for a survey of information to achieve validity. You know the limitations of things like anecdotal evidence, such that if that is the best you've got you at least understand the ramifications thereof. Reliability implies multiple repetitions of the same test, while validity requires certain sample sizes and other elements that the researcher can control (Phelan & Wren, 2006).

Part 2.

8. Ensuring that the objectives of the analysis are clear and consistent with the decision requires is a process before any information -- gathering. The organisation's starting point must be some sort of strategic objective, and the information would therefore be structured around the idea of supporting that objective. Basically, you can only ask the right questions if you already have thought about what answers you need -- that part comes first.

9. Cause and effect are sometimes difficult to determine empirically. It is not hard to outline correlation, but causation is a different matter entirely. The logical chain of events is less logical in real life. The biggest thing here is to understand the limitations to the correlation. If you want to prove causation, the data-gathering has to be specifically oriented towards that, to ask it, to measure it from the beginning. If not, the best thing to do is accept that this is a limitation in the research (Srivasta, 2015).

10. Statistical analysis is critical for understanding data. First, you need someone conversant in statistics to do this -- others can cobble it together but the interpretation of data will not be strong enough. Excel can run an ANOVA, but it is usually preferred to work with a more robust statistical package like SPSS. Ensure that the information you seek is conducive to statistical data -- again having someone on staff that can design queries, understand limitations and otherwise make a strong contribution to the statistical rigour of any research is important.

11. Sensitivity analysis is interesting because it requires guesswork -- estimates of future outcomes. So in that sense, it's GIGO work. If your assumptions are trash, your research outcomes will be, too. But a sensitivity analysis just means running the test over multiple different conditions to see how the outcome of the test reacts to changes in a number of different variables (Investopedia, 2016).

12. Documentation should always reflect a logical approach to evidence and conclusions drawn. Ensuring this is a quality control function -- somebody needs to go into the documentation and look at it to make sure that it follows a logical approach and uses evidence. This is not necessarily going to be the case every time so it is the role of the supervisor to ensure that proper documentation is undertaken at all times, providing both carrot and stick motivators to ensure that this is the case.

13. A lot of management information systems have some flexibility with respect to their dashboards and with respect to how they gather information. So it is important to ensure that the software you are using for business intelligence is customizable to meet your needs. A system of periodic review of such application is necessary to ensure that they are meeting your needs, and if they are not if that is a matter of training, or if you should look at competing systems.

14. It can be a challenge to ensure that decisions are made using data. So to build that transparency, documentation is recommended. Decisions, and the process that leads up to them, can be documented, and when they are that provides evidence that data when into the decision-making process. The act of documenting alone will compel more people to ensure that they have a rational, empirical case to support their decision-making, so writing it down ends up being a self-fulfilling prophecy in that respect.

15. Risk management plans are interesting in the sense that they can help to put risk into perspective. Where possible, decisions should include a risk analysis where people from different key internal stakeholder groups evaluate a situation, the damage that might arise in different situations of failure, and what the cost of that failure might thus be. The transparency mentioned above is important because it really helps to dial managers in on accurate risk assessment.

16. Quantitative methods were discussed in question 14 -- that's what reliable evidence is. Statistical training for both analysts and for final decision-makers is an important part of ensuring that quality quantitative analysis is used in decision-making.

17. Consultants would be used on an ad hoc basis to supplement existing organisational capabilities, filling in gaps in organisational expertise.

18. It is actually more valuable to empower people to make decisions they are capable of making, rather than enforcing a chain of command, which seems to be what this question is implying. Hire good people, let them do their jobs and make decisions. It's that simple.

19. Decisions, however, should be justifiable on the basis of both evidence and of organisational guidelines. When the decision is documented, it should be noted at that point in time how the decision is aligned with organisational guidelines, especially if the decision is non-routine.

20.This is basically the same answer as #19 -- the organisation writes all of this stuff down, and the manager making the decision can refer back to it to ensure that the organisation is adhering to the various guidelines, objectives, or whatever else the decision is being tested against.

21. There are ways to ensure that decision are made within a timely manner. First is to have something to manage workflow, like Asana or a similar tool for task management. The second is to build a culture of ensuring that decision are made in a timely manner. If the company has a culture where deadlines are never fixed, and can always be pushed back, then in that company nobody will stick to deadlines. If deadlines in the culture are hard, and people treat them as such, then that is the sort of culture where decisions will consistently be made by deadline. When culture holds people accountable for their behavior, they are more likely to behave the way the company wants them to.

22. As noted earlier, a documentation platform is required to ensure that information is documented in a consistent, repeatable manner. But also mentioned previously, it is important that there is some sort of documentation culture such that the people who would reference this information expect that it will be documented, and can figure out fairly easily where it has been documented. Without that, it will not be all that valuable to write everything down -- people still need to know that it is written down, and where to find it.

23. A documentation culture is essential to ensuring that documentation is done regularly. The point for this is that the organisation has to build in this culture. People need to document everything, and do it as a matter of course, not as something that they might do at some future point in time. There are ways to build a culture around documentation -- things like gamification or other means of creating incentives can encourage everybody within the organisation to document effectively.

24. To design systems to meet the requirements of decision-makers, it is critical that the requirements of decision-makers are understood. This can actually be challenging, because often the decision-makers cannot sufficiently articulate what their requirements are. So it can be a bit of an iterative process where the product is run past the decision-maker for testing and the decision-maker returns input. But often, it is better just to start at the very beginning with interviewing key decision-makers to ensure that there is as much information as possible about what the key decision-maker might want or need out of the project.

25. Ensuring information is up-to-date actually reflects back to the previous answers about creating a culture around documentation. If that is done, then it is fairly easy to know that all of the information is up-to-date. But there still is a challenge where it comes to ensuring that information entered previously is up-to-date. For that, one of the documentation challenges is to write down when something is entered into the system when it might become stale-dated. It may also be valuable to take slower periods and go over critical pieces of information and ensure that they remain documented properly.