 1. Database Integration
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| Probability: | 4 |
| Impact: | 4 |
| Mitigating Strategy: |
Integrating with an unknown database is
a complicated task due to the difference in table layouts, missing required data, and extraneous data.
That is why integrating with the store’s database for customer information, inventory, and sales is a
major risk. The probability is 4 because this is very likely to happen, and the impact is also 4 because
if we are unable to integrate the database, we cannot deliver a system with all of Sous Chef’s features.
Mitigating this risk seems like a daunting
task at first, but upon closer examination, the task is not that difficult. The Sous Chef team will
implement an integration system that will allow the team to import data from a database regardless of
its source. At the beginning of the integration process, database schemas will be exchanged with the
grocery store. After the field properties are discussed and agreed upon, the store will send us an
updated data in a flat file format at the scheduled times via an ftp process. We will place a batch
job to grab these files and write stored-procedures to translate, validate and import the data into the
appropriate tables of the Sous Chef database. |
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2. Database Performance |
| Probability: | 2 |
| Impact: | 4 |
| Mitigating Strategy: |
Having a database is useful, but if the
database does not perform well, its usefulness declines rapidly. The database needs to be designed with
the system’s complexity in mind. The traffic coming in and out of the database will be high due to the
number of users accessing the system and queries requested daily; therefore, the database must be designed
with performance as a high priority. The probability of this risk is 2 because the database will be
designed with high performance in mind at an early stage. However, the impact is 4 because if the
developer fails to create a robust database, the system will suffer and customers will be unhappy due to
its slow performance.
The Sous Chef team plans on mitigating this
risk by focusing on database performance at the beginning of the product’s developmental stage. We will
consult a database expert during the development process who will assist, analyze and suggest a plan to
create a well designed and robust database structure that can handle the heavy load of data processing.
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3. Database scalability |
| Probability: | 2 |
| Impact: | 3 |
| Mitigating Strategy: |
In order for Sous Chef to be successful,
the database must also be flexible to handle many concurrent users and an increasing number of users. The
ability of a system to handle both small and large numbers of users is called its scalability. If Sous
Chef is not scalable, the store’s use for Sous Chef is not scalable. Due to the possibility of a large
user increase over a short period of time, the probability is 2. However, the impact is only 3 because
the problem can be resolved quickly without any significant impact on the system or the budget.
We plan on mitigating this risk by designing
the database and associated servers to be interchangeable and load-balancing. That means that servers can
be added as needed and the load will be equally distributed amongst all the servers. That will increase
scalability by increasing the ability of the overall system to bear the load of more users.
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4. Test Data Consistency |
| Probability: | 3 |
| Impact: | 2 |
| Mitigating Strategy: |
Because we will not be purchasing
the recipe database until Phase II, we will be creating a set of pseudo recipes for database testing
in Phase I. We plan to write a program to generate a set of pseudo recipes in order to test the system.
The risk in generating pseudo data is that the data characteristics might not be consistent with the
real data. The probability of this risk is 3 because we do not have the domain knowledge to know the
distribution of recipe information. However, the impact is only 2 because the recipe data characteristics
can be changed without too much difficulty in Phase II.
This risk can be mitigated by conforming
the testing to data processing and performance and not to the properties of the recipe information.
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5. FDA Guideline Changes |
| Probability: | 1 |
| Impact: | 3 |
| Mitigating Strategy: |
The FDA has been known to change its
dietary recommendations, especially in recent years. This could affect Sous Chef adversely if the FDA
requires a new piece of nutritional information that we do not already have stored in our database.
The probability for this risk is only 1 because the FDA does not change their dietary recommendations
frequently. Also, we will be able to modify our database to adapt to the changes before it adversely
affects the product. The impact can be as high as 3 because we might be giving our customer incorrect
or incomplete data and the changes might require the database tables to change.
We plan to mitigate this risk by contracting
the recipe company to be responsible for modifying the recipes according to FDA’s rules and regulations
and supply us with an updated recipe database. We will also have a full time dietician in Phase 3 who
will ensure that our recipes are up-to-date with all the FDA’s dietary guidelines and recommendations.
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6. Database Storage |
| Probability: | 1 |
| Impact: | 2 |
| Mitigating Strategy: |
If our database has inadequate storage,
we will be unable to store all of the recipes or customer information. This means that the database will
not be able to solve the problem. The risk probability is only 1 because we estimate the database storage
requirement to be about 2 gigabytes while each database server, of which there are two, has 80 gigabytes
of storage. That means we have a total storage capacity of 160 gigabytes. The impact is a 2 because we
can simply add more storage to our servers to solve the problem with only a minimal impact to the budget.
This risk is mitigated by carefully analyzing
the hardware need for when the product is fully implemented and functioning. After the analysis, we
will purchase adequate hardware to accommodate future storage increase. We will also monitor and analyze
the system usage frequently to prevent any inadequate resource problems.
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Risks Analysis Diagram |
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